statsmodels →
0.11.1-2 →
armhf → 2020-04-28 13:31:50
sbuild (Debian sbuild) 0.71.0 (24 Aug 2016) on bm-wb-04
+==============================================================================+
| statsmodels 0.11.1-2 (armhf) Tue, 28 Apr 2020 07:12:53 +0000 |
+==============================================================================+
Package: statsmodels
Version: 0.11.1-2
Source Version: 0.11.1-2
Distribution: bullseye-staging
Machine Architecture: armhf
Host Architecture: armhf
Build Architecture: armhf
I: NOTICE: Log filtering will replace 'var/lib/schroot/mount/bullseye-staging-armhf-sbuild-1729eb96-51c6-41bd-b414-a20f2ac2513a' with '<<CHROOT>>'
+------------------------------------------------------------------------------+
| Update chroot |
+------------------------------------------------------------------------------+
Get:1 http://172.17.0.1/private bullseye-staging InRelease [11.3 kB]
Get:2 http://172.17.0.1/private bullseye-staging/main Sources [11.7 MB]
Get:3 http://172.17.0.1/private bullseye-staging/main armhf Packages [12.8 MB]
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Reading package lists...
W: No sandbox user '_apt' on the system, can not drop privileges
+------------------------------------------------------------------------------+
| Fetch source files |
+------------------------------------------------------------------------------+
Check APT
---------
Checking available source versions...
Download source files with APT
------------------------------
Reading package lists...
NOTICE: 'statsmodels' packaging is maintained in the 'Git' version control system at:
https://salsa.debian.org/science-team/statsmodels.git
Please use:
git clone https://salsa.debian.org/science-team/statsmodels.git
to retrieve the latest (possibly unreleased) updates to the package.
Need to get 11.6 MB of source archives.
Get:1 http://172.17.0.1/private bullseye-staging/main statsmodels 0.11.1-2 (dsc) [3442 B]
Get:2 http://172.17.0.1/private bullseye-staging/main statsmodels 0.11.1-2 (tar) [11.6 MB]
Get:3 http://172.17.0.1/private bullseye-staging/main statsmodels 0.11.1-2 (diff) [33.0 kB]
Fetched 11.6 MB in 1s (11.2 MB/s)
Download complete and in download only mode
I: NOTICE: Log filtering will replace 'build/statsmodels-gUHiHo/statsmodels-0.11.1' with '<<PKGBUILDDIR>>'
I: NOTICE: Log filtering will replace 'build/statsmodels-gUHiHo' with '<<BUILDDIR>>'
+------------------------------------------------------------------------------+
| Install build-essential |
+------------------------------------------------------------------------------+
Setup apt archive
-----------------
Merged Build-Depends: build-essential, fakeroot
Filtered Build-Depends: build-essential, fakeroot
dpkg-deb: building package 'sbuild-build-depends-core-dummy' in '/<<BUILDDIR>>/resolver-LHdrnh/apt_archive/sbuild-build-depends-core-dummy.deb'.
dpkg-scanpackages: warning: Packages in archive but missing from override file:
dpkg-scanpackages: warning: sbuild-build-depends-core-dummy
dpkg-scanpackages: info: Wrote 1 entries to output Packages file.
gpg: keybox '/<<BUILDDIR>>/resolver-LHdrnh/gpg/pubring.kbx' created
gpg: /<<BUILDDIR>>/resolver-LHdrnh/gpg/trustdb.gpg: trustdb created
gpg: key 35506D9A48F77B2E: public key "Sbuild Signer (Sbuild Build Dependency Archive Key) <buildd-tools-devel@lists.alioth.debian.org>" imported
gpg: Total number processed: 1
gpg: imported: 1
gpg: key 35506D9A48F77B2E: "Sbuild Signer (Sbuild Build Dependency Archive Key) <buildd-tools-devel@lists.alioth.debian.org>" not changed
gpg: key 35506D9A48F77B2E: secret key imported
gpg: Total number processed: 1
gpg: unchanged: 1
gpg: secret keys read: 1
gpg: secret keys imported: 1
gpg: using "Sbuild Signer" as default secret key for signing
Ign:1 copy:/<<BUILDDIR>>/resolver-LHdrnh/apt_archive ./ InRelease
Get:2 copy:/<<BUILDDIR>>/resolver-LHdrnh/apt_archive ./ Release [957 B]
Get:3 copy:/<<BUILDDIR>>/resolver-LHdrnh/apt_archive ./ Release.gpg [370 B]
Get:4 copy:/<<BUILDDIR>>/resolver-LHdrnh/apt_archive ./ Sources [349 B]
Get:5 copy:/<<BUILDDIR>>/resolver-LHdrnh/apt_archive ./ Packages [433 B]
Fetched 2109 B in 1s (2658 B/s)
Reading package lists...
W: No sandbox user '_apt' on the system, can not drop privileges
Reading package lists...
Install core build dependencies (apt-based resolver)
----------------------------------------------------
Installing build dependencies
Reading package lists...
Building dependency tree...
Reading state information...
The following packages were automatically installed and are no longer required:
libpam-cap netbase
Use 'apt autoremove' to remove them.
The following NEW packages will be installed:
sbuild-build-depends-core-dummy
0 upgraded, 1 newly installed, 0 to remove and 18 not upgraded.
Need to get 852 B of archives.
After this operation, 0 B of additional disk space will be used.
Get:1 copy:/<<BUILDDIR>>/resolver-LHdrnh/apt_archive ./ sbuild-build-depends-core-dummy 0.invalid.0 [852 B]
debconf: delaying package configuration, since apt-utils is not installed
Fetched 852 B in 0s (22.9 kB/s)
Selecting previously unselected package sbuild-build-depends-core-dummy.
(Reading database ... 12224 files and directories currently installed.)
Preparing to unpack .../sbuild-build-depends-core-dummy_0.invalid.0_armhf.deb ...
Unpacking sbuild-build-depends-core-dummy (0.invalid.0) ...
Setting up sbuild-build-depends-core-dummy (0.invalid.0) ...
W: No sandbox user '_apt' on the system, can not drop privileges
+------------------------------------------------------------------------------+
| Check architectures |
+------------------------------------------------------------------------------+
Arch check ok (armhf included in any all)
+------------------------------------------------------------------------------+
| Install package build dependencies |
+------------------------------------------------------------------------------+
Setup apt archive
-----------------
Merged Build-Depends: debhelper-compat (= 12), sphinx-common, dh-python (>= 3.20180313~), cython3, python3-all-dev, python3-colorama, python3-cvxopt, python3-dateutil, python3-joblib, python3-matplotlib, python3-numpy, python3-pandas, python3-patsy (>= 0.5.1), python3-pytest, python3-scipy, python3-setuptools, python3-tk
Filtered Build-Depends: debhelper-compat (= 12), sphinx-common, dh-python (>= 3.20180313~), cython3, python3-all-dev, python3-colorama, python3-cvxopt, python3-dateutil, python3-joblib, python3-matplotlib, python3-numpy, python3-pandas, python3-patsy (>= 0.5.1), python3-pytest, python3-scipy, python3-setuptools, python3-tk
dpkg-deb: building package 'sbuild-build-depends-statsmodels-dummy' in '/<<BUILDDIR>>/resolver-LHdrnh/apt_archive/sbuild-build-depends-statsmodels-dummy.deb'.
dpkg-scanpackages: warning: Packages in archive but missing from override file:
dpkg-scanpackages: warning: sbuild-build-depends-core-dummy sbuild-build-depends-statsmodels-dummy
dpkg-scanpackages: info: Wrote 2 entries to output Packages file.
gpg: using "Sbuild Signer" as default secret key for signing
Ign:1 copy:/<<BUILDDIR>>/resolver-LHdrnh/apt_archive ./ InRelease
Get:2 copy:/<<BUILDDIR>>/resolver-LHdrnh/apt_archive ./ Release [963 B]
Get:3 copy:/<<BUILDDIR>>/resolver-LHdrnh/apt_archive ./ Release.gpg [370 B]
Get:4 copy:/<<BUILDDIR>>/resolver-LHdrnh/apt_archive ./ Sources [642 B]
Get:5 copy:/<<BUILDDIR>>/resolver-LHdrnh/apt_archive ./ Packages [703 B]
Fetched 2678 B in 1s (3524 B/s)
Reading package lists...
W: No sandbox user '_apt' on the system, can not drop privileges
Reading package lists...
Install statsmodels build dependencies (apt-based resolver)
-----------------------------------------------------------
Installing build dependencies
Reading package lists...
Building dependency tree...
Reading state information...
The following packages were automatically installed and are no longer required:
libpam-cap netbase
Use 'apt autoremove' to remove them.
The following additional packages will be installed:
autoconf automake autopoint autotools-dev blt bsdmainutils cython3 debhelper
dh-autoreconf dh-python dh-strip-nondeterminism dwz file fontconfig-config
fonts-lyx gcc-10-base gettext gettext-base groff-base intltool-debian
libamd2 libarchive-zip-perl libatomic1 libblas3 libbsd0 libcamd2 libcc1-0
libccolamd2 libcholmod3 libcolamd2 libcroco3 libdebhelper-perl libdsdp-5.8gf
libelf1 libexpat1 libexpat1-dev libfftw3-double3
libfile-stripnondeterminism-perl libfontconfig1 libfreetype6 libgcc-s1
libgcc1 libgfortran5 libglib2.0-0 libglpk40 libgomp1 libgsl23 libgslcblas0
libicu63 libjs-jquery libjs-jquery-ui libjs-sphinxdoc libjs-underscore
liblapack3 liblbfgsb0 libltdl7 libmagic-mgc libmagic1 libmetis5 libmpdec2
libncurses6 libpipeline1 libpng16-16 libprocps8 libpython3-all-dev
libpython3-dev libpython3-stdlib libpython3.7-minimal libpython3.7-stdlib
libpython3.8 libpython3.8-dev libpython3.8-minimal libpython3.8-stdlib
libsigsegv2 libssl1.1 libstdc++6 libsub-override-perl libsuitesparseconfig5
libtcl8.6 libtinfo5 libtk8.6 libtool libubsan1 libuchardet0 libumfpack5
libx11-6 libx11-data libxau6 libxcb1 libxdmcp6 libxext6 libxft2 libxml2
libxrender1 libxss1 m4 man-db mime-support po-debconf procps
python-matplotlib-data python3 python3-all python3-all-dev
python3-atomicwrites python3-attr python3-colorama python3-cvxopt
python3-cycler python3-dateutil python3-decorator python3-dev
python3-distutils python3-importlib-metadata python3-joblib
python3-kiwisolver python3-lib2to3 python3-matplotlib python3-minimal
python3-more-itertools python3-numpy python3-packaging python3-pandas
python3-pandas-lib python3-patsy python3-pkg-resources python3-pluggy
python3-py python3-pyparsing python3-pytest python3-scipy python3-setuptools
python3-six python3-tk python3-tz python3-wcwidth python3-zipp python3.7
python3.7-minimal python3.8 python3.8-dev python3.8-minimal sensible-utils
sphinx-common tk8.6-blt2.5 ttf-bitstream-vera ucf x11-common zlib1g-dev
Suggested packages:
autoconf-archive gnu-standards autoconf-doc blt-demo wamerican | wordlist
whois vacation cython-doc dh-make gettext-doc libasprintf-dev
libgettextpo-dev groff libfftw3-bin libfftw3-dev libiodbc2-dev
default-libmysqlclient-dev gsl-ref-psdoc | gsl-doc-pdf | gsl-doc-info
| gsl-ref-html libjs-jquery-ui-docs tcl8.6 tk8.6 libtool-doc gfortran
| fortran95-compiler gcj-jdk m4-doc apparmor less www-browser
libmail-box-perl python3-doc python3-venv python-attr-doc python-cvxopt-doc
python-cycler-doc dvipng ffmpeg ghostscript gir1.2-gtk-3.0 inkscape ipython3
librsvg2-common python-matplotlib-doc python3-cairocffi python3-gi
python3-gi-cairo python3-gobject python3-nose python3-pyqt5 python3-sip
python3-tornado texlive-extra-utils texlive-latex-extra ttf-staypuft
gfortran python-numpy-doc python3-numpy-dbg python-pandas-doc
python3-statsmodels python-patsy-doc subversion python-pyparsing-doc
python-scipy-doc python-setuptools-doc tix python3-tk-dbg python3.7-venv
python3.7-doc binfmt-support python3.8-venv python3.8-doc
Recommended packages:
curl | wget | lynx libarchive-cpio-perl libglib2.0-data shared-mime-info
xdg-user-dirs javascript-common libgpm2 libltdl-dev libmail-sendmail-perl
psmisc python3-simplejson python3-psutil python3-pil python3-numexpr
python3-tables python3-xlrd python3-openpyxl python3-xlwt python3-bs4
python3-html5lib python3-lxml python3-sphinx
The following NEW packages will be installed:
autoconf automake autopoint autotools-dev blt bsdmainutils cython3 debhelper
dh-autoreconf dh-python dh-strip-nondeterminism dwz file fontconfig-config
fonts-lyx gettext gettext-base groff-base intltool-debian libamd2
libarchive-zip-perl libblas3 libbsd0 libcamd2 libccolamd2 libcholmod3
libcolamd2 libcroco3 libdebhelper-perl libdsdp-5.8gf libelf1 libexpat1
libexpat1-dev libfftw3-double3 libfile-stripnondeterminism-perl
libfontconfig1 libfreetype6 libgfortran5 libglib2.0-0 libglpk40 libgsl23
libgslcblas0 libicu63 libjs-jquery libjs-jquery-ui libjs-sphinxdoc
libjs-underscore liblapack3 liblbfgsb0 libltdl7 libmagic-mgc libmagic1
libmetis5 libmpdec2 libncurses6 libpipeline1 libpng16-16 libprocps8
libpython3-all-dev libpython3-dev libpython3-stdlib libpython3.7-minimal
libpython3.7-stdlib libpython3.8 libpython3.8-dev libpython3.8-minimal
libpython3.8-stdlib libsigsegv2 libssl1.1 libsub-override-perl
libsuitesparseconfig5 libtcl8.6 libtinfo5 libtk8.6 libtool libuchardet0
libumfpack5 libx11-6 libx11-data libxau6 libxcb1 libxdmcp6 libxext6 libxft2
libxml2 libxrender1 libxss1 m4 man-db mime-support po-debconf procps
python-matplotlib-data python3 python3-all python3-all-dev
python3-atomicwrites python3-attr python3-colorama python3-cvxopt
python3-cycler python3-dateutil python3-decorator python3-dev
python3-distutils python3-importlib-metadata python3-joblib
python3-kiwisolver python3-lib2to3 python3-matplotlib python3-minimal
python3-more-itertools python3-numpy python3-packaging python3-pandas
python3-pandas-lib python3-patsy python3-pkg-resources python3-pluggy
python3-py python3-pyparsing python3-pytest python3-scipy python3-setuptools
python3-six python3-tk python3-tz python3-wcwidth python3-zipp python3.7
python3.7-minimal python3.8 python3.8-dev python3.8-minimal
sbuild-build-depends-statsmodels-dummy sensible-utils sphinx-common
tk8.6-blt2.5 ttf-bitstream-vera ucf x11-common zlib1g-dev
The following packages will be upgraded:
gcc-10-base libatomic1 libcc1-0 libgcc-s1 libgcc1 libgomp1 libstdc++6
libubsan1
8 upgraded, 142 newly installed, 0 to remove and 10 not upgraded.
Need to get 128 MB of archives.
After this operation, 412 MB of additional disk space will be used.
Get:1 copy:/<<BUILDDIR>>/resolver-LHdrnh/apt_archive ./ sbuild-build-depends-statsmodels-dummy 0.invalid.0 [984 B]
Get:2 http://172.17.0.1/private bullseye-staging/main armhf libbsd0 armhf 0.10.0-1 [112 kB]
Get:3 http://172.17.0.1/private bullseye-staging/main armhf libtinfo5 armhf 6.2-1 [318 kB]
Get:4 http://172.17.0.1/private bullseye-staging/main armhf bsdmainutils armhf 11.1.2 [182 kB]
Get:5 http://172.17.0.1/private bullseye-staging/main armhf libatomic1 armhf 10-20200418-1+rpi1 [8188 B]
Get:6 http://172.17.0.1/private bullseye-staging/main armhf libubsan1 armhf 10-20200418-1+rpi1 [115 kB]
Get:7 http://172.17.0.1/private bullseye-staging/main armhf gcc-10-base armhf 10-20200418-1+rpi1 [197 kB]
Get:8 http://172.17.0.1/private bullseye-staging/main armhf libstdc++6 armhf 10-20200418-1+rpi1 [408 kB]
Get:9 http://172.17.0.1/private bullseye-staging/main armhf libgomp1 armhf 10-20200418-1+rpi1 [82.9 kB]
Get:10 http://172.17.0.1/private bullseye-staging/main armhf libgcc1 armhf 1:10-20200418-1+rpi1 [36.0 kB]
Get:11 http://172.17.0.1/private bullseye-staging/main armhf libcc1-0 armhf 10-20200418-1+rpi1 [31.7 kB]
Get:12 http://172.17.0.1/private bullseye-staging/main armhf libgcc-s1 armhf 10-20200418-1+rpi1 [36.1 kB]
Get:13 http://172.17.0.1/private bullseye-staging/main armhf libuchardet0 armhf 0.0.6-3 [62.2 kB]
Get:14 http://172.17.0.1/private bullseye-staging/main armhf groff-base armhf 1.22.4-4 [783 kB]
Get:15 http://172.17.0.1/private bullseye-staging/main armhf libpipeline1 armhf 1.5.2-2 [29.6 kB]
Get:16 http://172.17.0.1/private bullseye-staging/main armhf man-db armhf 2.9.1-1 [1262 kB]
Get:17 http://172.17.0.1/private bullseye-staging/main armhf libssl1.1 armhf 1.1.1g-1 [1272 kB]
Get:18 http://172.17.0.1/private bullseye-staging/main armhf libpython3.8-minimal armhf 3.8.2-1 [744 kB]
Get:19 http://172.17.0.1/private bullseye-staging/main armhf libexpat1 armhf 2.2.9-1 [71.5 kB]
Get:20 http://172.17.0.1/private bullseye-staging/main armhf python3.8-minimal armhf 3.8.2-1 [1628 kB]
Get:21 http://172.17.0.1/private bullseye-staging/main armhf python3-minimal armhf 3.8.2-3 [37.6 kB]
Get:22 http://172.17.0.1/private bullseye-staging/main armhf mime-support all 3.64 [37.8 kB]
Get:23 http://172.17.0.1/private bullseye-staging/main armhf libmpdec2 armhf 2.4.2-3 [68.1 kB]
Get:24 http://172.17.0.1/private bullseye-staging/main armhf libpython3.8-stdlib armhf 3.8.2-1 [1597 kB]
Get:25 http://172.17.0.1/private bullseye-staging/main armhf python3.8 armhf 3.8.2-1 [410 kB]
Get:26 http://172.17.0.1/private bullseye-staging/main armhf libpython3-stdlib armhf 3.8.2-3 [20.8 kB]
Get:27 http://172.17.0.1/private bullseye-staging/main armhf python3 armhf 3.8.2-3 [63.7 kB]
Get:28 http://172.17.0.1/private bullseye-staging/main armhf libpython3.7-minimal armhf 3.7.7-1 [585 kB]
Get:29 http://172.17.0.1/private bullseye-staging/main armhf python3.7-minimal armhf 3.7.7-1 [1532 kB]
Get:30 http://172.17.0.1/private bullseye-staging/main armhf libncurses6 armhf 6.2-1 [79.5 kB]
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Get:32 http://172.17.0.1/private bullseye-staging/main armhf procps armhf 2:3.3.16-4 [238 kB]
Get:33 http://172.17.0.1/private bullseye-staging/main armhf sensible-utils all 0.0.12+nmu1 [16.0 kB]
Get:34 http://172.17.0.1/private bullseye-staging/main armhf libmagic-mgc armhf 1:5.38-4 [262 kB]
Get:35 http://172.17.0.1/private bullseye-staging/main armhf libmagic1 armhf 1:5.38-4 [112 kB]
Get:36 http://172.17.0.1/private bullseye-staging/main armhf file armhf 1:5.38-4 [66.9 kB]
Get:37 http://172.17.0.1/private bullseye-staging/main armhf gettext-base armhf 0.19.8.1-10 [117 kB]
Get:38 http://172.17.0.1/private bullseye-staging/main armhf ucf all 3.0038+nmu1 [69.0 kB]
Get:39 http://172.17.0.1/private bullseye-staging/main armhf libsigsegv2 armhf 2.12-2 [32.3 kB]
Get:40 http://172.17.0.1/private bullseye-staging/main armhf m4 armhf 1.4.18-4 [185 kB]
Get:41 http://172.17.0.1/private bullseye-staging/main armhf autoconf all 2.69-11.1 [341 kB]
Get:42 http://172.17.0.1/private bullseye-staging/main armhf autotools-dev all 20180224.1 [77.0 kB]
Get:43 http://172.17.0.1/private bullseye-staging/main armhf automake all 1:1.16.2-1 [775 kB]
Get:44 http://172.17.0.1/private bullseye-staging/main armhf autopoint all 0.19.8.1-10 [435 kB]
Get:45 http://172.17.0.1/private bullseye-staging/main armhf libtcl8.6 armhf 8.6.10+dfsg-1 [886 kB]
Get:46 http://172.17.0.1/private bullseye-staging/main armhf libpng16-16 armhf 1.6.37-2 [274 kB]
Get:47 http://172.17.0.1/private bullseye-staging/main armhf libfreetype6 armhf 2.10.1-2 [330 kB]
Get:48 http://172.17.0.1/private bullseye-staging/main armhf ttf-bitstream-vera all 1.10-8 [352 kB]
Get:49 http://172.17.0.1/private bullseye-staging/main armhf fontconfig-config all 2.13.1-4 [281 kB]
Get:50 http://172.17.0.1/private bullseye-staging/main armhf libfontconfig1 armhf 2.13.1-4 [328 kB]
Get:51 http://172.17.0.1/private bullseye-staging/main armhf libxau6 armhf 1:1.0.8-1+b2 [19.1 kB]
Get:52 http://172.17.0.1/private bullseye-staging/main armhf libxdmcp6 armhf 1:1.1.2-3 [25.0 kB]
Get:53 http://172.17.0.1/private bullseye-staging/main armhf libxcb1 armhf 1.14-2 [135 kB]
Get:54 http://172.17.0.1/private bullseye-staging/main armhf libx11-data all 2:1.6.9-2 [298 kB]
Get:55 http://172.17.0.1/private bullseye-staging/main armhf libx11-6 armhf 2:1.6.9-2 [692 kB]
Get:56 http://172.17.0.1/private bullseye-staging/main armhf libxrender1 armhf 1:0.9.10-1 [29.9 kB]
Get:57 http://172.17.0.1/private bullseye-staging/main armhf libxft2 armhf 2.3.2-2 [49.3 kB]
Get:58 http://172.17.0.1/private bullseye-staging/main armhf libxext6 armhf 2:1.3.3-1+b2 [47.8 kB]
Get:59 http://172.17.0.1/private bullseye-staging/main armhf x11-common all 1:7.7+20 [252 kB]
Get:60 http://172.17.0.1/private bullseye-staging/main armhf libxss1 armhf 1:1.2.3-1 [17.3 kB]
Get:61 http://172.17.0.1/private bullseye-staging/main armhf libtk8.6 armhf 8.6.10-1 [678 kB]
Get:62 http://172.17.0.1/private bullseye-staging/main armhf tk8.6-blt2.5 armhf 2.5.3+dfsg-4 [468 kB]
Get:63 http://172.17.0.1/private bullseye-staging/main armhf blt armhf 2.5.3+dfsg-4 [14.8 kB]
Get:64 http://172.17.0.1/private bullseye-staging/main armhf cython3 armhf 0.29.14-1 [1398 kB]
Get:65 http://172.17.0.1/private bullseye-staging/main armhf libtool all 2.4.6-14 [513 kB]
Get:66 http://172.17.0.1/private bullseye-staging/main armhf dh-autoreconf all 19 [16.9 kB]
Get:67 http://172.17.0.1/private bullseye-staging/main armhf libdebhelper-perl all 13 [184 kB]
Get:68 http://172.17.0.1/private bullseye-staging/main armhf libarchive-zip-perl all 1.68-1 [104 kB]
Get:69 http://172.17.0.1/private bullseye-staging/main armhf libsub-override-perl all 0.09-2 [10.2 kB]
Get:70 http://172.17.0.1/private bullseye-staging/main armhf libfile-stripnondeterminism-perl all 1.8.0-1 [24.2 kB]
Get:71 http://172.17.0.1/private bullseye-staging/main armhf dh-strip-nondeterminism all 1.8.0-1 [14.8 kB]
Get:72 http://172.17.0.1/private bullseye-staging/main armhf libelf1 armhf 0.176-1.1 [158 kB]
Get:73 http://172.17.0.1/private bullseye-staging/main armhf dwz armhf 0.13-5 [142 kB]
Get:74 http://172.17.0.1/private bullseye-staging/main armhf libglib2.0-0 armhf 2.64.2-1 [1158 kB]
Get:75 http://172.17.0.1/private bullseye-staging/main armhf libicu63 armhf 63.2-3 [7987 kB]
Get:76 http://172.17.0.1/private bullseye-staging/main armhf libxml2 armhf 2.9.10+dfsg-5 [592 kB]
Get:77 http://172.17.0.1/private bullseye-staging/main armhf libcroco3 armhf 0.6.13-1 [133 kB]
Get:78 http://172.17.0.1/private bullseye-staging/main armhf gettext armhf 0.19.8.1-10 [1219 kB]
Get:79 http://172.17.0.1/private bullseye-staging/main armhf intltool-debian all 0.35.0+20060710.5 [26.8 kB]
Get:80 http://172.17.0.1/private bullseye-staging/main armhf po-debconf all 1.0.21 [248 kB]
Get:81 http://172.17.0.1/private bullseye-staging/main armhf debhelper all 13 [1002 kB]
Get:82 http://172.17.0.1/private bullseye-staging/main armhf python3-lib2to3 all 3.8.2-2 [78.4 kB]
Get:83 http://172.17.0.1/private bullseye-staging/main armhf python3-distutils all 3.8.2-2 [145 kB]
Get:84 http://172.17.0.1/private bullseye-staging/main armhf dh-python all 4.20200315 [91.6 kB]
Get:85 http://172.17.0.1/private bullseye-staging/main armhf fonts-lyx all 2.3.4.2-2 [200 kB]
Get:86 http://172.17.0.1/private bullseye-staging/main armhf libsuitesparseconfig5 armhf 1:5.7.2+dfsg-1 [22.1 kB]
Get:87 http://172.17.0.1/private bullseye-staging/main armhf libamd2 armhf 1:5.7.2+dfsg-1 [28.8 kB]
Get:88 http://172.17.0.1/private bullseye-staging/main armhf libblas3 armhf 3.9.0-2 [108 kB]
Get:89 http://172.17.0.1/private bullseye-staging/main armhf libcamd2 armhf 1:5.7.2+dfsg-1 [29.3 kB]
Get:90 http://172.17.0.1/private bullseye-staging/main armhf libccolamd2 armhf 1:5.7.2+dfsg-1 [30.0 kB]
Get:91 http://172.17.0.1/private bullseye-staging/main armhf libcolamd2 armhf 1:5.7.2+dfsg-1 [26.8 kB]
Get:92 http://172.17.0.1/private bullseye-staging/main armhf libgfortran5 armhf 10-20200418-1+rpi1 [231 kB]
Get:93 http://172.17.0.1/private bullseye-staging/main armhf liblapack3 armhf 3.9.0-2 [1602 kB]
Get:94 http://172.17.0.1/private bullseye-staging/main armhf libmetis5 armhf 5.1.0.dfsg-5 [131 kB]
Get:95 http://172.17.0.1/private bullseye-staging/main armhf libcholmod3 armhf 1:5.7.2+dfsg-1 [212 kB]
Get:96 http://172.17.0.1/private bullseye-staging/main armhf libexpat1-dev armhf 2.2.9-1 [119 kB]
Get:97 http://172.17.0.1/private bullseye-staging/main armhf libfftw3-double3 armhf 3.3.8-2 [429 kB]
Get:98 http://172.17.0.1/private bullseye-staging/main armhf libltdl7 armhf 2.4.6-14 [388 kB]
Get:99 http://172.17.0.1/private bullseye-staging/main armhf libglpk40 armhf 4.65-2 [339 kB]
Get:100 http://172.17.0.1/private bullseye-staging/main armhf libgslcblas0 armhf 2.5+dfsg-6 [79.0 kB]
Get:101 http://172.17.0.1/private bullseye-staging/main armhf libgsl23 armhf 2.5+dfsg-6 [704 kB]
Get:102 http://172.17.0.1/private bullseye-staging/main armhf libjs-jquery all 3.3.1~dfsg-3 [332 kB]
Get:103 http://172.17.0.1/private bullseye-staging/main armhf libjs-jquery-ui all 1.12.1+dfsg-5 [232 kB]
Get:104 http://172.17.0.1/private bullseye-staging/main armhf libjs-underscore all 1.9.1~dfsg-1 [99.4 kB]
Get:105 http://172.17.0.1/private bullseye-staging/main armhf libjs-sphinxdoc all 2.4.3-2 [110 kB]
Get:106 http://172.17.0.1/private bullseye-staging/main armhf liblbfgsb0 armhf 3.0+dfsg.3-8 [25.5 kB]
Get:107 http://172.17.0.1/private bullseye-staging/main armhf libpython3.8 armhf 3.8.2-1 [1367 kB]
Get:108 http://172.17.0.1/private bullseye-staging/main armhf libpython3.8-dev armhf 3.8.2-1 [46.0 MB]
Get:109 http://172.17.0.1/private bullseye-staging/main armhf libpython3-dev armhf 3.8.2-3 [21.0 kB]
Get:110 http://172.17.0.1/private bullseye-staging/main armhf libpython3-all-dev armhf 3.8.2-3 [1068 B]
Get:111 http://172.17.0.1/private bullseye-staging/main armhf libpython3.7-stdlib armhf 3.7.7-1 [1670 kB]
Get:112 http://172.17.0.1/private bullseye-staging/main armhf libumfpack5 armhf 1:5.7.2+dfsg-1 [127 kB]
Get:113 http://172.17.0.1/private bullseye-staging/main armhf python-matplotlib-data all 3.2.1-1 [4145 kB]
Get:114 http://172.17.0.1/private bullseye-staging/main armhf python3-all armhf 3.8.2-3 [1056 B]
Get:115 http://172.17.0.1/private bullseye-staging/main armhf zlib1g-dev armhf 1:1.2.11.dfsg-2 [184 kB]
Get:116 http://172.17.0.1/private bullseye-staging/main armhf python3.8-dev armhf 3.8.2-1 [533 kB]
Get:117 http://172.17.0.1/private bullseye-staging/main armhf python3-dev armhf 3.8.2-3 [1164 B]
Get:118 http://172.17.0.1/private bullseye-staging/main armhf python3-all-dev armhf 3.8.2-3 [1064 B]
Get:119 http://172.17.0.1/private bullseye-staging/main armhf python3-atomicwrites all 1.1.5-4 [7136 B]
Get:120 http://172.17.0.1/private bullseye-staging/main armhf python3-attr all 19.3.0-4 [43.3 kB]
Get:121 http://172.17.0.1/private bullseye-staging/main armhf python3-colorama all 0.4.3-1 [27.8 kB]
Get:122 http://172.17.0.1/private bullseye-staging/main armhf libdsdp-5.8gf armhf 5.8-9.4 [136 kB]
Get:123 http://172.17.0.1/private bullseye-staging/main armhf python3-cvxopt armhf 1.2.3+dfsg-2+b1 [261 kB]
Get:124 http://172.17.0.1/private bullseye-staging/main armhf python3-six all 1.14.0-3 [16.7 kB]
Get:125 http://172.17.0.1/private bullseye-staging/main armhf python3-cycler all 0.10.0-3 [8084 B]
Get:126 http://172.17.0.1/private bullseye-staging/main armhf python3-dateutil all 2.8.1-4 [81.6 kB]
Get:127 http://172.17.0.1/private bullseye-staging/main armhf python3-decorator all 4.4.2-2 [15.8 kB]
Get:128 http://172.17.0.1/private bullseye-staging/main armhf python3-more-itertools all 4.2.0-2 [42.6 kB]
Get:129 http://172.17.0.1/private bullseye-staging/main armhf python3-zipp all 1.0.0-2 [5984 B]
Get:130 http://172.17.0.1/private bullseye-staging/main armhf python3-importlib-metadata all 1.5.0-2 [10.1 kB]
Get:131 http://172.17.0.1/private bullseye-staging/main armhf python3-pkg-resources all 44.0.0-1 [155 kB]
Get:132 http://172.17.0.1/private bullseye-staging/main armhf python3-joblib all 0.14.0-3 [203 kB]
Get:133 http://172.17.0.1/private bullseye-staging/main armhf python3-kiwisolver armhf 1.0.1-3 [245 kB]
Get:134 http://172.17.0.1/private bullseye-staging/main armhf python3-pyparsing all 2.4.6-2 [109 kB]
Get:135 http://172.17.0.1/private bullseye-staging/main armhf python3.7 armhf 3.7.7-1 [354 kB]
Get:136 http://172.17.0.1/private bullseye-staging/main armhf python3-numpy armhf 1:1.17.4-5+b1 [4484 kB]
Get:137 http://172.17.0.1/private bullseye-staging/main armhf python3-matplotlib armhf 3.2.1-1 [4617 kB]
Get:138 http://172.17.0.1/private bullseye-staging/main armhf python3-packaging all 20.3-1.2 [29.9 kB]
Get:139 http://172.17.0.1/private bullseye-staging/main armhf python3-tz all 2019.3-2 [27.3 kB]
Get:140 http://172.17.0.1/private bullseye-staging/main armhf python3-pandas-lib armhf 0.25.3+dfsg-9+rpi1 [7002 kB]
Get:141 http://172.17.0.1/private bullseye-staging/main armhf python3-pandas all 0.25.3+dfsg-9+rpi1 [1984 kB]
Get:142 http://172.17.0.1/private bullseye-staging/main armhf python3-patsy all 0.5.1-1 [172 kB]
Get:143 http://172.17.0.1/private bullseye-staging/main armhf python3-pluggy all 0.13.0-4 [22.0 kB]
Get:144 http://172.17.0.1/private bullseye-staging/main armhf python3-py all 1.8.1-2 [86.8 kB]
Get:145 http://172.17.0.1/private bullseye-staging/main armhf python3-wcwidth all 0.1.8+dfsg1-5 [17.7 kB]
Get:146 http://172.17.0.1/private bullseye-staging/main armhf python3-pytest all 4.6.9-3 [267 kB]
Get:147 http://172.17.0.1/private bullseye-staging/main armhf python3-scipy armhf 1.3.3-3+b1 [12.1 MB]
Get:148 http://172.17.0.1/private bullseye-staging/main armhf python3-setuptools all 44.0.0-1 [313 kB]
Get:149 http://172.17.0.1/private bullseye-staging/main armhf python3-tk armhf 3.8.2-2 [107 kB]
Get:150 http://172.17.0.1/private bullseye-staging/main armhf sphinx-common all 2.4.3-2 [550 kB]
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update-rc.d: warning: start and stop actions are no longer supported; falling back to defaults
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Setting up dh-python (4.20200315) ...
Setting up python3-more-itertools (4.2.0-2) ...
Setting up python3-attr (19.3.0-4) ...
Setting up python3.7 (3.7.7-1) ...
Setting up gettext (0.19.8.1-10) ...
Setting up python3-setuptools (44.0.0-1) ...
Setting up libxrender1:armhf (1:0.9.10-1) ...
Setting up python3-py (1.8.1-2) ...
Setting up python3-joblib (0.14.0-3) ...
Setting up python3-colorama (0.4.3-1) ...
Setting up fontconfig-config (2.13.1-4) ...
Setting up libxext6:armhf (2:1.3.3-1+b2) ...
Setting up python3-all (3.8.2-3) ...
Setting up python3-zipp (1.0.0-2) ...
Setting up man-db (2.9.1-1) ...
Not building database; man-db/auto-update is not 'true'.
Setting up intltool-debian (0.35.0+20060710.5) ...
Setting up python3-packaging (20.3-1.2) ...
Setting up libumfpack5:armhf (1:5.7.2+dfsg-1) ...
Setting up libpython3.8-dev:armhf (3.8.2-1) ...
Setting up sphinx-common (2.4.3-2) ...
Setting up python3-kiwisolver (1.0.1-3) ...
Setting up python3-numpy (1:1.17.4-5+b1) ...
Setting up python3.8-dev (3.8.2-1) ...
Setting up libxss1:armhf (1:1.2.3-1) ...
Setting up libfontconfig1:armhf (2.13.1-4) ...
Setting up python3-matplotlib (3.2.1-1) ...
Setting up libxft2:armhf (2.3.2-2) ...
Setting up python3-scipy (1.3.3-3+b1) ...
Setting up libpython3-dev:armhf (3.8.2-3) ...
Setting up python3-importlib-metadata (1.5.0-2) ...
Setting up python3-cvxopt (1.2.3+dfsg-2+b1) ...
/usr/lib/python3/dist-packages/cvxopt/__init__.py:136: SyntaxWarning: "is" with a literal. Did you mean "=="?
if val is 0: val = None
/usr/lib/python3/dist-packages/cvxopt/coneprog.py:4043: SyntaxWarning: "is" with a literal. Did you mean "=="?
if status is 'optimal' or dcost <= 0.0:
/usr/lib/python3/dist-packages/cvxopt/coneprog.py:4061: SyntaxWarning: "is" with a literal. Did you mean "=="?
if status is 'optimal' or pcost >= 0.0:
/usr/lib/python3/dist-packages/cvxopt/misc.py:916: SyntaxWarning: "is" with a literal. Did you mean "=="?
if diag is 'N':
/usr/lib/python3/dist-packages/cvxopt/msk.py:105: SyntaxWarning: "is" with a literal. Did you mean "=="?
if m is 0: raise ValueError("m cannot be 0")
/usr/lib/python3/dist-packages/cvxopt/msk.py:178: SyntaxWarning: "is not" with a literal. Did you mean "!="?
if p is not 0:
/usr/lib/python3/dist-packages/cvxopt/msk.py:314: SyntaxWarning: "is" with a literal. Did you mean "=="?
if cdim is 0: raise ValueError("ml+mq+ms cannot be 0")
/usr/lib/python3/dist-packages/cvxopt/msk.py:750: SyntaxWarning: "is" with a literal. Did you mean "=="?
if m+p is 0: raise ValueError("m + p must be greater than 0")
/usr/lib/python3/dist-packages/cvxopt/msk.py:815: SyntaxWarning: "is not" with a literal. Did you mean "!="?
if m is not 0:
/usr/lib/python3/dist-packages/cvxopt/msk.py:823: SyntaxWarning: "is not" with a literal. Did you mean "!="?
if p is not 0:
/usr/lib/python3/dist-packages/cvxopt/msk.py:904: SyntaxWarning: "is" with a literal. Did you mean "=="?
if m is 0: raise ValueError("m cannot be 0")
/usr/lib/python3/dist-packages/cvxopt/printing.py:43: SyntaxWarning: "is" with a literal. Did you mean "=="?
if width*height is 0: return ""
/usr/lib/python3/dist-packages/cvxopt/printing.py:44: SyntaxWarning: "is" with a literal. Did you mean "=="?
if len(X) is 0: return ""
/usr/lib/python3/dist-packages/cvxopt/printing.py:101: SyntaxWarning: "is" with a literal. Did you mean "=="?
if width*height is 0: return ""
Setting up po-debconf (1.0.21) ...
Setting up libtk8.6:armhf (8.6.10-1) ...
Setting up python3-pandas-lib (0.25.3+dfsg-9+rpi1) ...
Setting up python3-patsy (0.5.1-1) ...
Setting up python3-pandas (0.25.3+dfsg-9+rpi1) ...
/usr/lib/python3/dist-packages/pandas/tests/frame/test_alter_axes.py:241: SyntaxWarning: "is" with a literal. Did you mean "=="?
False if (keys[0] is "A" and keys[1] is "A") else drop # noqa: F632
/usr/lib/python3/dist-packages/pandas/tests/frame/test_alter_axes.py:241: SyntaxWarning: "is" with a literal. Did you mean "=="?
False if (keys[0] is "A" and keys[1] is "A") else drop # noqa: F632
Setting up libpython3-all-dev:armhf (3.8.2-3) ...
Setting up python3-dev (3.8.2-3) ...
Setting up python3-pluggy (0.13.0-4) ...
Setting up python3-all-dev (3.8.2-3) ...
Setting up tk8.6-blt2.5 (2.5.3+dfsg-4) ...
Setting up python3-pytest (4.6.9-3) ...
Setting up blt (2.5.3+dfsg-4) ...
Setting up python3-tk:armhf (3.8.2-2) ...
Setting up dh-autoreconf (19) ...
Setting up debhelper (13) ...
Setting up sbuild-build-depends-statsmodels-dummy (0.invalid.0) ...
Processing triggers for libc-bin (2.30-4+rpi1) ...
W: No sandbox user '_apt' on the system, can not drop privileges
+------------------------------------------------------------------------------+
| Build environment |
+------------------------------------------------------------------------------+
Kernel: Linux 4.9.0-0.bpo.4-armmp armhf (armv7l)
Toolchain package versions: binutils_2.34-5+rpi1 dpkg-dev_1.19.7 g++-9_9.3.0-10+rpi1 gcc-9_9.3.0-10+rpi1 libc6-dev_2.30-4+rpi1 libstdc++-9-dev_9.3.0-10+rpi1 libstdc++6_10-20200418-1+rpi1 linux-libc-dev_5.2.17-1+rpi1+b2
Package versions: adduser_3.118 apt_2.0.2 autoconf_2.69-11.1 automake_1:1.16.2-1 autopoint_0.19.8.1-10 autotools-dev_20180224.1 base-files_11+rpi1 base-passwd_3.5.47 bash_5.0-6 binutils_2.34-5+rpi1 binutils-arm-linux-gnueabihf_2.34-5+rpi1 binutils-common_2.34-5+rpi1 blt_2.5.3+dfsg-4 bsdmainutils_11.1.2 bsdutils_1:2.34-0.1 build-essential_12.8 bzip2_1.0.8-2 coreutils_8.30-3 cpp_4:9.2.1-3.1+rpi1 cpp-9_9.3.0-10+rpi1 cython3_0.29.14-1 dash_0.5.10.2-7 debconf_1.5.73 debhelper_13 debianutils_4.9.1 dh-autoreconf_19 dh-python_4.20200315 dh-strip-nondeterminism_1.8.0-1 diffutils_1:3.7-3 dirmngr_2.2.20-1 dpkg_1.19.7 dpkg-dev_1.19.7 dwz_0.13-5 e2fsprogs_1.45.6-1 fakeroot_1.24-1 fdisk_2.34-0.1 file_1:5.38-4 findutils_4.7.0-1 fontconfig-config_2.13.1-4 fonts-lyx_2.3.4.2-2 g++_4:9.2.1-3.1+rpi1 g++-9_9.3.0-10+rpi1 gcc_4:9.2.1-3.1+rpi1 gcc-10-base_10-20200418-1+rpi1 gcc-9_9.3.0-10+rpi1 gcc-9-base_9.3.0-10+rpi1 gettext_0.19.8.1-10 gettext-base_0.19.8.1-10 gnupg_2.2.20-1 gnupg-l10n_2.2.20-1 gnupg-utils_2.2.20-1 gpg_2.2.20-1 gpg-agent_2.2.20-1 gpg-wks-client_2.2.20-1 gpg-wks-server_2.2.20-1 gpgconf_2.2.20-1 gpgsm_2.2.20-1 gpgv_2.2.20-1 grep_3.4-1 groff-base_1.22.4-4 gzip_1.10-2 hostname_3.23 init-system-helpers_1.57 intltool-debian_0.35.0+20060710.5 iputils-ping_3:20190709-3 libacl1_2.2.53-6 libamd2_1:5.7.2+dfsg-1 libapt-pkg6.0_2.0.2 libarchive-zip-perl_1.68-1 libasan5_9.3.0-10+rpi1 libassuan0_2.5.3-7 libatomic1_10-20200418-1+rpi1 libattr1_1:2.4.48-5 libaudit-common_1:2.8.5-3 libaudit1_1:2.8.5-3 libbinutils_2.34-5+rpi1 libblas3_3.9.0-2 libblkid1_2.34-0.1 libbsd0_0.10.0-1 libbz2-1.0_1.0.8-2 libc-bin_2.30-4+rpi1 libc-dev-bin_2.30-4+rpi1 libc6_2.30-4+rpi1 libc6-dev_2.30-4+rpi1 libcamd2_1:5.7.2+dfsg-1 libcap-ng0_0.7.9-2.1+b1 libcap2_1:2.33-1 libcap2-bin_1:2.33-1 libcc1-0_10-20200418-1+rpi1 libccolamd2_1:5.7.2+dfsg-1 libcholmod3_1:5.7.2+dfsg-1 libcolamd2_1:5.7.2+dfsg-1 libcom-err2_1.45.6-1 libcroco3_0.6.13-1 libcrypt-dev_1:4.4.16-1 libcrypt1_1:4.4.16-1 libctf-nobfd0_2.34-5+rpi1 libctf0_2.34-5+rpi1 libdb5.3_5.3.28+dfsg1-0.6 libdebconfclient0_0.251 libdebhelper-perl_13 libdpkg-perl_1.19.7 libdsdp-5.8gf_5.8-9.4 libelf1_0.176-1.1 libexpat1_2.2.9-1 libexpat1-dev_2.2.9-1 libext2fs2_1.45.6-1 libfakeroot_1.24-1 libfdisk1_2.34-0.1 libffi7_3.3-4 libfftw3-double3_3.3.8-2 libfile-stripnondeterminism-perl_1.8.0-1 libfontconfig1_2.13.1-4 libfreetype6_2.10.1-2 libgcc-9-dev_9.3.0-10+rpi1 libgcc-s1_10-20200418-1+rpi1 libgcc1_1:10-20200418-1+rpi1 libgcrypt20_1.8.5-5 libgdbm-compat4_1.18.1-5 libgdbm6_1.18.1-5 libgfortran5_10-20200418-1+rpi1 libglib2.0-0_2.64.2-1 libglpk40_4.65-2 libgmp10_2:6.2.0+dfsg-4 libgnutls30_3.6.13-2 libgomp1_10-20200418-1+rpi1 libgpg-error0_1.37-1 libgsl23_2.5+dfsg-6 libgslcblas0_2.5+dfsg-6 libhogweed5_3.5.1+really3.5.1-2 libicu63_63.2-3 libidn2-0_2.3.0-1 libisl22_0.22.1-1 libjs-jquery_3.3.1~dfsg-3 libjs-jquery-ui_1.12.1+dfsg-5 libjs-sphinxdoc_2.4.3-2 libjs-underscore_1.9.1~dfsg-1 libksba8_1.3.5-2 liblapack3_3.9.0-2 liblbfgsb0_3.0+dfsg.3-8 libldap-2.4-2_2.4.49+dfsg-2 libldap-common_2.4.49+dfsg-3 libltdl7_2.4.6-14 liblz4-1_1.9.2-2 liblzma5_5.2.4-1 libmagic-mgc_1:5.38-4 libmagic1_1:5.38-4 libmetis5_5.1.0.dfsg-5 libmount1_2.34-0.1 libmpc3_1.1.0-1 libmpdec2_2.4.2-3 libmpfr6_4.0.2-1 libncurses6_6.2-1 libncursesw6_6.2-1 libnettle7_3.5.1+really3.5.1-2 libnpth0_1.6-1 libp11-kit0_0.23.20-1 libpam-cap_1:2.33-1 libpam-modules_1.3.1-5 libpam-modules-bin_1.3.1-5 libpam-runtime_1.3.1-5 libpam0g_1.3.1-5 libpcre2-8-0_10.34-7 libpcre3_2:8.39-12 libperl5.30_5.30.0-9 libpipeline1_1.5.2-2 libpng16-16_1.6.37-2 libprocps8_2:3.3.16-4 libpython3-all-dev_3.8.2-3 libpython3-dev_3.8.2-3 libpython3-stdlib_3.8.2-3 libpython3.7-minimal_3.7.7-1 libpython3.7-stdlib_3.7.7-1 libpython3.8_3.8.2-1 libpython3.8-dev_3.8.2-1 libpython3.8-minimal_3.8.2-1 libpython3.8-stdlib_3.8.2-1 libreadline7_7.0-5 libreadline8_8.0-4 libsasl2-2_2.1.27+dfsg-2 libsasl2-modules-db_2.1.27+dfsg-2 libseccomp2_2.4.3-1+rpi1 libselinux1_3.0-1+b1 libsemanage-common_3.0-1 libsemanage1_3.0-1+b1 libsepol1_3.0-1 libsigsegv2_2.12-2 libsmartcols1_2.34-0.1 libsqlite3-0_3.31.1-4 libss2_1.45.6-1 libssl1.1_1.1.1g-1 libstdc++-9-dev_9.3.0-10+rpi1 libstdc++6_10-20200418-1+rpi1 libsub-override-perl_0.09-2 libsuitesparseconfig5_1:5.7.2+dfsg-1 libsystemd0_244.3-1+rpi1 libtasn1-6_4.16.0-2 libtcl8.6_8.6.10+dfsg-1 libtinfo5_6.2-1 libtinfo6_6.2-1 libtk8.6_8.6.10-1 libtool_2.4.6-14 libubsan1_10-20200418-1+rpi1 libuchardet0_0.0.6-3 libudev1_244.3-1+rpi1 libumfpack5_1:5.7.2+dfsg-1 libunistring2_0.9.10-2 libuuid1_2.34-0.1 libx11-6_2:1.6.9-2 libx11-data_2:1.6.9-2 libxau6_1:1.0.8-1+b2 libxcb1_1.14-2 libxdmcp6_1:1.1.2-3 libxext6_2:1.3.3-1+b2 libxft2_2.3.2-2 libxml2_2.9.10+dfsg-5 libxrender1_1:0.9.10-1 libxss1_1:1.2.3-1 libzstd1_1.4.4+dfsg-3+rpi1 linux-libc-dev_5.2.17-1+rpi1+b2 login_1:4.8.1-1 logsave_1.45.6-1 lsb-base_11.1.0+rpi1 m4_1.4.18-4 make_4.2.1-1.2 man-db_2.9.1-1 mawk_1.3.4.20200120-2 mime-support_3.64 mount_2.34-0.1 ncurses-base_6.2-1 ncurses-bin_6.2-1 netbase_6.1 passwd_1:4.8.1-1 patch_2.7.6-6 perl_5.30.0-9 perl-base_5.30.0-9 perl-modules-5.30_5.30.0-9 pinentry-curses_1.1.0-3 po-debconf_1.0.21 procps_2:3.3.16-4 python-matplotlib-data_3.2.1-1 python3_3.8.2-3 python3-all_3.8.2-3 python3-all-dev_3.8.2-3 python3-atomicwrites_1.1.5-4 python3-attr_19.3.0-4 python3-colorama_0.4.3-1 python3-cvxopt_1.2.3+dfsg-2+b1 python3-cycler_0.10.0-3 python3-dateutil_2.8.1-4 python3-decorator_4.4.2-2 python3-dev_3.8.2-3 python3-distutils_3.8.2-2 python3-importlib-metadata_1.5.0-2 python3-joblib_0.14.0-3 python3-kiwisolver_1.0.1-3 python3-lib2to3_3.8.2-2 python3-matplotlib_3.2.1-1 python3-minimal_3.8.2-3 python3-more-itertools_4.2.0-2 python3-numpy_1:1.17.4-5+b1 python3-packaging_20.3-1.2 python3-pandas_0.25.3+dfsg-9+rpi1 python3-pandas-lib_0.25.3+dfsg-9+rpi1 python3-patsy_0.5.1-1 python3-pkg-resources_44.0.0-1 python3-pluggy_0.13.0-4 python3-py_1.8.1-2 python3-pyparsing_2.4.6-2 python3-pytest_4.6.9-3 python3-scipy_1.3.3-3+b1 python3-setuptools_44.0.0-1 python3-six_1.14.0-3 python3-tk_3.8.2-2 python3-tz_2019.3-2 python3-wcwidth_0.1.8+dfsg1-5 python3-zipp_1.0.0-2 python3.7_3.7.7-1 python3.7-minimal_3.7.7-1 python3.8_3.8.2-1 python3.8-dev_3.8.2-1 python3.8-minimal_3.8.2-1 raspbian-archive-keyring_20120528.2 readline-common_8.0-4 sbuild-build-depends-core-dummy_0.invalid.0 sbuild-build-depends-statsmodels-dummy_0.invalid.0 sed_4.7-1 sensible-utils_0.0.12+nmu1 sphinx-common_2.4.3-2 sysvinit-utils_2.96-3 tar_1.30+dfsg-7 tk8.6-blt2.5_2.5.3+dfsg-4 ttf-bitstream-vera_1.10-8 tzdata_2019c-3 ucf_3.0038+nmu1 util-linux_2.34-0.1 x11-common_1:7.7+20 xz-utils_5.2.4-1 zlib1g_1:1.2.11.dfsg-2 zlib1g-dev_1:1.2.11.dfsg-2
+------------------------------------------------------------------------------+
| Build |
+------------------------------------------------------------------------------+
Unpack source
-------------
gpgv: unknown type of key resource 'trustedkeys.kbx'
gpgv: keyblock resource '/sbuild-nonexistent/.gnupg/trustedkeys.kbx': General error
gpgv: Signature made Sat Apr 25 19:05:36 2020 UTC
gpgv: using RSA key 67CB311005C4EDBE32175308DEE50D0D567EA266
gpgv: issuer "rebecca_palmer@zoho.com"
gpgv: Can't check signature: No public key
dpkg-source: warning: failed to verify signature on ./statsmodels_0.11.1-2.dsc
dpkg-source: info: extracting statsmodels in /<<PKGBUILDDIR>>
dpkg-source: info: unpacking statsmodels_0.11.1.orig.tar.gz
dpkg-source: info: unpacking statsmodels_0.11.1-2.debian.tar.xz
dpkg-source: info: using patch list from debian/patches/series
dpkg-source: info: applying use-cached-datasets
dpkg-source: info: applying up_reduce_test_precision
dpkg-source: info: applying use-system-inventory
dpkg-source: info: applying xfail_kalman_armhf.patch
dpkg-source: info: applying use_available_data.patch
dpkg-source: info: applying i386_loosen_test_tolerances.patch
dpkg-source: info: applying python3_shebangs.patch
dpkg-source: info: applying use_tmp_path.patch
dpkg-source: info: applying 944054_flaky_tests.patch
dpkg-source: info: applying sphinx_autosummary.patch
dpkg-source: info: applying up5253_gee_offset.patch
dpkg-source: info: applying no_sphinx_material.patch
dpkg-source: info: applying sphinx_ignore_errors.patch
dpkg-source: info: applying fix_test_bounds.patch
dpkg-source: info: applying sphinx_local_requirejs.patch
dpkg-source: info: applying spelling.patch
dpkg-source: info: applying dont_require_warnings.patch
dpkg-source: info: applying xfail_regimeswitching_armhf.patch
dpkg-source: info: applying xfail_dynamicfactor_ppc64el.patch
dpkg-source: info: applying xfail_no_multiprocessing.patch
dpkg-source: info: applying remove_ccbysa_snippet.patch
Check disc space
----------------
Sufficient free space for build
User Environment
----------------
APT_CONFIG=/var/lib/sbuild/apt.conf
DEB_BUILD_OPTIONS=parallel=4
HOME=/sbuild-nonexistent
LC_ALL=POSIX
LOGNAME=buildd
PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games
SCHROOT_ALIAS_NAME=bullseye-staging-armhf-sbuild
SCHROOT_CHROOT_NAME=bullseye-staging-armhf-sbuild
SCHROOT_COMMAND=env
SCHROOT_GID=109
SCHROOT_GROUP=buildd
SCHROOT_SESSION_ID=bullseye-staging-armhf-sbuild-1729eb96-51c6-41bd-b414-a20f2ac2513a
SCHROOT_UID=104
SCHROOT_USER=buildd
SHELL=/bin/sh
TERM=linux
USER=buildd
dpkg-buildpackage
-----------------
dpkg-buildpackage: info: source package statsmodels
dpkg-buildpackage: info: source version 0.11.1-2
dpkg-buildpackage: info: source distribution unstable
dpkg-source --before-build .
dpkg-buildpackage: info: host architecture armhf
debian/rules clean
dh clean --with python3,sphinxdoc --buildsystem=pybuild
debian/rules override_dh_auto_clean
make[1]: Entering directory '/<<PKGBUILDDIR>>'
# this would try to run setup.py clean, which is an error: dh_auto_clean
rm -rf cythonize.dat \
*.egg-info \
*.png \
.pybuild \
.pytest_cache \
build \
docs/build/ \
docs/rehab.table \
docs/salary.table \
docs/source/datasets/generated \
docs/source/examples/notebooks \
docs/source/savefig \
docs/source/dev/generated \
docs/source/datasets/statsmodels.datasets.*.rst \
docs/source/examples/notebooks/generated \
examples/executed \
tools/hash_dict.pickle
find . -name __pycache__ -print0 | xargs -0 rm -rf
find . -name *.pyx -print0 | sed -e "s/\.pyx/.c/g" | xargs -0 rm -f
find . -name *.pyx.in -print0 | sed -e "s/\.pyx\.in/.pyx/g" | xargs -0 rm -f
: # Remove autogenerated version.py
rm -f statsmodels/version.py
make[1]: Leaving directory '/<<PKGBUILDDIR>>'
dh_autoreconf_clean -O--buildsystem=pybuild
dh_clean -O--buildsystem=pybuild
debian/rules binary-arch
dh binary-arch --with python3,sphinxdoc --buildsystem=pybuild
dh_update_autotools_config -a -O--buildsystem=pybuild
dh_autoreconf -a -O--buildsystem=pybuild
dh_auto_configure -a -O--buildsystem=pybuild
I: pybuild base:217: python3.8 setup.py config
Compiling statsmodels/tsa/_stl.pyx because it changed.
Compiling statsmodels/tsa/_exponential_smoothers.pyx because it changed.
Compiling statsmodels/tsa/_innovations.pyx because it changed.
Compiling statsmodels/tsa/regime_switching/_hamilton_filter.pyx because it changed.
Compiling statsmodels/tsa/regime_switching/_kim_smoother.pyx because it changed.
Compiling statsmodels/tsa/innovations/_arma_innovations.pyx because it changed.
Compiling statsmodels/nonparametric/linbin.pyx because it changed.
Compiling statsmodels/nonparametric/_smoothers_lowess.pyx because it changed.
Compiling statsmodels/tsa/kalmanf/kalman_loglike.pyx because it changed.
Compiling statsmodels/tsa/statespace/_initialization.pyx because it changed.
Compiling statsmodels/tsa/statespace/_representation.pyx because it changed.
Compiling statsmodels/tsa/statespace/_kalman_filter.pyx because it changed.
Compiling statsmodels/tsa/statespace/_filters/_conventional.pyx because it changed.
Compiling statsmodels/tsa/statespace/_filters/_inversions.pyx because it changed.
Compiling statsmodels/tsa/statespace/_filters/_univariate.pyx because it changed.
Compiling statsmodels/tsa/statespace/_filters/_univariate_diffuse.pyx because it changed.
Compiling statsmodels/tsa/statespace/_kalman_smoother.pyx because it changed.
Compiling statsmodels/tsa/statespace/_smoothers/_alternative.pyx because it changed.
Compiling statsmodels/tsa/statespace/_smoothers/_classical.pyx because it changed.
Compiling statsmodels/tsa/statespace/_smoothers/_conventional.pyx because it changed.
Compiling statsmodels/tsa/statespace/_smoothers/_univariate.pyx because it changed.
Compiling statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx because it changed.
Compiling statsmodels/tsa/statespace/_simulation_smoother.pyx because it changed.
Compiling statsmodels/tsa/statespace/_tools.pyx because it changed.
[ 1/24] Cythonizing statsmodels/nonparametric/_smoothers_lowess.pyx
[ 2/24] Cythonizing statsmodels/nonparametric/linbin.pyx
[ 3/24] Cythonizing statsmodels/tsa/_exponential_smoothers.pyx
[ 4/24] Cythonizing statsmodels/tsa/_innovations.pyx
[ 5/24] Cythonizing statsmodels/tsa/_stl.pyx
[ 6/24] Cythonizing statsmodels/tsa/innovations/_arma_innovations.pyx
[ 7/24] Cythonizing statsmodels/tsa/kalmanf/kalman_loglike.pyx
[ 8/24] Cythonizing statsmodels/tsa/regime_switching/_hamilton_filter.pyx
[ 9/24] Cythonizing statsmodels/tsa/regime_switching/_kim_smoother.pyx
[10/24] Cythonizing statsmodels/tsa/statespace/_filters/_conventional.pyx
[11/24] Cythonizing statsmodels/tsa/statespace/_filters/_inversions.pyx
[12/24] Cythonizing statsmodels/tsa/statespace/_filters/_univariate.pyx
[13/24] Cythonizing statsmodels/tsa/statespace/_filters/_univariate_diffuse.pyx
[14/24] Cythonizing statsmodels/tsa/statespace/_initialization.pyx
[15/24] Cythonizing statsmodels/tsa/statespace/_kalman_filter.pyx
[16/24] Cythonizing statsmodels/tsa/statespace/_kalman_smoother.pyx
[17/24] Cythonizing statsmodels/tsa/statespace/_representation.pyx
[18/24] Cythonizing statsmodels/tsa/statespace/_simulation_smoother.pyx
[19/24] Cythonizing statsmodels/tsa/statespace/_smoothers/_alternative.pyx
[20/24] Cythonizing statsmodels/tsa/statespace/_smoothers/_classical.pyx
[21/24] Cythonizing statsmodels/tsa/statespace/_smoothers/_conventional.pyx
[22/24] Cythonizing statsmodels/tsa/statespace/_smoothers/_univariate.pyx
[23/24] Cythonizing statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx
[24/24] Cythonizing statsmodels/tsa/statespace/_tools.pyx
running config
warning: statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx:555:14: Unreachable code
warning: statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx:1130:14: Unreachable code
warning: statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx:1705:14: Unreachable code
warning: statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx:2280:14: Unreachable code
debian/rules override_dh_auto_build-arch
make[1]: Entering directory '/<<PKGBUILDDIR>>'
mkdir "/<<PKGBUILDDIR>>/build"
: # Hardcode backend to Agg to avoid doc build and tests failures
echo "backend : Agg" >| /<<PKGBUILDDIR>>/build/matplotlibrc
dh_auto_build
I: pybuild base:217: /usr/bin/python3 setup.py build
running build
running build_py
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels
copying statsmodels/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels
copying statsmodels/_version.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels
copying statsmodels/api.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels
copying statsmodels/conftest.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/_constraints.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/_parameter_inference.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/_penalized.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/_penalties.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/_screening.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/covtype.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/data.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/distributed_estimation.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/elastic_net.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/l1_cvxopt.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/l1_slsqp.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/l1_solvers_common.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/model.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/optimizer.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/transform.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
copying statsmodels/base/wrapper.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/compat
copying statsmodels/compat/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/compat
copying statsmodels/compat/numpy.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/compat
copying statsmodels/compat/pandas.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/compat
copying statsmodels/compat/platform.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/compat
copying statsmodels/compat/python.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/compat
copying statsmodels/compat/scipy.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/compat
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/datasets
copying statsmodels/datasets/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/datasets
copying statsmodels/datasets/template_data.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/datasets
copying statsmodels/datasets/utils.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/datasets
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete
copying statsmodels/discrete/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete
copying statsmodels/discrete/_diagnostics_count.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete
copying statsmodels/discrete/conditional_models.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete
copying statsmodels/discrete/count_model.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete
copying statsmodels/discrete/discrete_margins.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete
copying statsmodels/discrete/discrete_model.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/distributions
copying statsmodels/distributions/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/distributions
copying statsmodels/distributions/discrete.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/distributions
copying statsmodels/distributions/edgeworth.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/distributions
copying statsmodels/distributions/empirical_distribution.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/distributions
copying statsmodels/distributions/mixture_rvs.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/distributions
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/duration
copying statsmodels/duration/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/duration
copying statsmodels/duration/_kernel_estimates.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/duration
copying statsmodels/duration/api.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/duration
copying statsmodels/duration/hazard_regression.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/duration
copying statsmodels/duration/survfunc.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/duration
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/emplike
copying statsmodels/emplike/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/emplike
copying statsmodels/emplike/aft_el.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/emplike
copying statsmodels/emplike/api.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/emplike
copying statsmodels/emplike/descriptive.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/emplike
copying statsmodels/emplike/elanova.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/emplike
copying statsmodels/emplike/elregress.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/emplike
copying statsmodels/emplike/originregress.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/emplike
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/formula
copying statsmodels/formula/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/formula
copying statsmodels/formula/api.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/formula
copying statsmodels/formula/formulatools.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/formula
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/gam
copying statsmodels/gam/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/gam
copying statsmodels/gam/api.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/gam
copying statsmodels/gam/gam_penalties.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/gam
copying statsmodels/gam/generalized_additive_model.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/gam
copying statsmodels/gam/smooth_basis.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/gam
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod
copying statsmodels/genmod/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod
copying statsmodels/genmod/_prediction.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod
copying statsmodels/genmod/_tweedie_compound_poisson.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod
copying statsmodels/genmod/api.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod
copying statsmodels/genmod/bayes_mixed_glm.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod
copying statsmodels/genmod/cov_struct.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod
copying statsmodels/genmod/qif.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod
copying statsmodels/genmod/generalized_estimating_equations.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod
copying statsmodels/genmod/generalized_linear_model.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/_regressionplots_doc.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/agreement.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/api.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/boxplots.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/correlation.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/dotplots.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/factorplots.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/functional.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/gofplots.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/mosaicplot.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/plot_grids.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/plottools.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/tsaplots.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/tukeyplot.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/utils.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
copying statsmodels/graphics/regressionplots.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation
copying statsmodels/imputation/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation
copying statsmodels/imputation/bayes_mi.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation
copying statsmodels/imputation/mice.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation
copying statsmodels/imputation/ros.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/interface
copying statsmodels/interface/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/interface
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/iolib
copying statsmodels/iolib/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/iolib
copying statsmodels/iolib/api.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/iolib
copying statsmodels/iolib/foreign.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/iolib
copying statsmodels/iolib/openfile.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/iolib
copying statsmodels/iolib/smpickle.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/iolib
copying statsmodels/iolib/stata_summary_examples.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/iolib
copying statsmodels/iolib/summary.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/iolib
copying statsmodels/iolib/summary2.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/iolib
copying statsmodels/iolib/table.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/iolib
copying statsmodels/iolib/tableformatting.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/iolib
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/miscmodels
copying statsmodels/miscmodels/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/miscmodels
copying statsmodels/miscmodels/api.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/miscmodels
copying statsmodels/miscmodels/count.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/miscmodels
copying statsmodels/miscmodels/nonlinls.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/miscmodels
copying statsmodels/miscmodels/tmodel.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/miscmodels
copying statsmodels/miscmodels/try_mlecov.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/miscmodels
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/multivariate
copying statsmodels/multivariate/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/multivariate
copying statsmodels/multivariate/api.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/multivariate
copying statsmodels/multivariate/cancorr.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/multivariate
copying statsmodels/multivariate/factor.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/multivariate
copying statsmodels/multivariate/manova.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/multivariate
copying statsmodels/multivariate/multivariate_ols.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/multivariate
copying statsmodels/multivariate/pca.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/multivariate
copying statsmodels/multivariate/plots.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/multivariate
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric
copying statsmodels/nonparametric/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric
copying statsmodels/nonparametric/_kernel_base.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric
copying statsmodels/nonparametric/api.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric
copying statsmodels/nonparametric/bandwidths.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric
copying statsmodels/nonparametric/kde.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric
copying statsmodels/nonparametric/kdetools.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric
copying statsmodels/nonparametric/kernel_density.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric
copying statsmodels/nonparametric/kernel_regression.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric
copying statsmodels/nonparametric/kernels.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric
copying statsmodels/nonparametric/smoothers_lowess.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric
copying statsmodels/nonparametric/smoothers_lowess_old.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression
copying statsmodels/regression/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression
copying statsmodels/regression/_prediction.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression
copying statsmodels/regression/_tools.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression
copying statsmodels/regression/dimred.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression
copying statsmodels/regression/feasible_gls.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression
copying statsmodels/regression/linear_model.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression
copying statsmodels/regression/mixed_linear_model.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression
copying statsmodels/regression/process_regression.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression
copying statsmodels/regression/recursive_ls.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression
copying statsmodels/regression/rolling.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression
copying statsmodels/regression/quantile_regression.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/resampling
copying statsmodels/resampling/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/resampling
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copying statsmodels/tsa/tests/results/savedrvs.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/results
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests
copying statsmodels/tsa/vector_ar/tests/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests
copying statsmodels/tsa/vector_ar/tests/example_svar.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests
copying statsmodels/tsa/vector_ar/tests/test_coint.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests
copying statsmodels/tsa/vector_ar/tests/test_svar.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests
copying statsmodels/tsa/vector_ar/tests/test_var.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests
copying statsmodels/tsa/vector_ar/tests/test_var_jmulti.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests
copying statsmodels/tsa/vector_ar/tests/test_vecm.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/parse_jmulti_var_output.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/parse_jmulti_vecm_output.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/Matlab_results
copying statsmodels/tsa/vector_ar/tests/Matlab_results/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/Matlab_results
creating /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/results
copying statsmodels/tsa/vector_ar/tests/results/__init__.py -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/results
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copying statsmodels/stats/tests/results/influence_measures_bool_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/results
copying statsmodels/stats/tests/results/results_influence_logit.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/results
copying statsmodels/stats/tests/results/wspec1.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/results
copying statsmodels/stats/tests/results/wspec2.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/results
copying statsmodels/stats/tests/results/wspec3.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/results
copying statsmodels/stats/tests/results/wspec4.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/results
copying statsmodels/stats/tests/results/influence_lsdiag_R.json -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/results
copying statsmodels/stats/tests/results/data.dat -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/results
copying statsmodels/tsa/regime_switching/tests/results/mar_filardo.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/results
copying statsmodels/tsa/regime_switching/tests/results/results_predict_fedfunds.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/results
copying statsmodels/tsa/regime_switching/tests/results/results_predict_rgnp.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/results
copying statsmodels/tsa/statespace/tests/results/clark1989.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/exponential_smoothing_params.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/exponential_smoothing_predict.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/exponential_smoothing_states.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_clark1989_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_dynamic_factor_stata.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_exact_initial_common_level_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_exact_initial_common_level_restricted_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_exact_initial_dfm_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_exact_initial_local_level_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_exact_initial_local_linear_trend_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_exact_initial_local_linear_trend_missing_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_exact_initial_var1_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_exact_initial_var1_measurement_error_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_exact_initial_var1_missing_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_exact_initial_var1_mixed_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_intercepts_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_realgdpar_stata.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_sarimax_coverage.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing0.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing1.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing2.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing3.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing3_variates.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
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copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing5.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing6.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
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copying statsmodels/tsa/statespace/tests/results/results_smoothing3_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_smoothing_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_smoothing_generalobscov_R.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
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copying statsmodels/tsa/statespace/tests/results/results_var_stata.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
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copying statsmodels/tsa/statespace/tests/results/results_wpi1_ar3_matlab_ssm.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_wpi1_ar3_stata.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/results_wpi1_missing_ar3_matlab_ssm.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/manufac.dta -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
copying statsmodels/tsa/statespace/tests/results/sm-0.9-sarimax.pkl -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/results
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copying statsmodels/tsa/tests/results/AROLSConstantPredict.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/results
copying statsmodels/tsa/tests/results/AROLSNoConstantPredict.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/results
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copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
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copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realcons_realgdp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realcons_realinv.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
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copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
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copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realcons_realgdp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
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copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
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copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realgdp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realgdp_realinv.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realinv.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realcons.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realcons_realgdp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realcons_realinv.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realgdp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realgdp_realinv.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realinv.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realcons.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realcons_realgdp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realcons_realinv.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realgdp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realgdp_realinv.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realinv.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realcons.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realcons_realgdp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realcons_realinv.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realgdp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realgdp_realinv.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realinv.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_granger_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_granger_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_inst_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_inst_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_granger_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_granger_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_inst_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_inst_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_granger_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_granger_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_inst_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_inst_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_granger_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_granger_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_inst_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_inst_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_granger_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_granger_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_inst_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_inst_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_granger_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_granger_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_inst_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_inst_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_granger_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_granger_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_inst_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_inst_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_granger_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_granger_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_inst_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_inst_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_granger_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_granger_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_inst_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_inst_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_Sigmau.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_diag.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_fc5.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_granger_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_granger_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_inst_causality_dp_r.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_inst_causality_r_dp.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_ir.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_lagorder.txt -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/JMulTi_results
copying statsmodels/tsa/vector_ar/tests/Matlab_results/test_coint.csv -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/Matlab_results
copying statsmodels/tsa/vector_ar/tests/results/vars_results.npz -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/results
copying statsmodels/tsa/vector_ar/tests/results/e1.dat -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/results
copying statsmodels/tsa/vector_ar/tests/results/e2.dat -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/results
copying statsmodels/tsa/vector_ar/tests/results/e3.dat -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/results
copying statsmodels/tsa/vector_ar/tests/results/e4.dat -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/results
copying statsmodels/tsa/vector_ar/tests/results/e5.dat -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/results
copying statsmodels/tsa/vector_ar/tests/results/e6.dat -> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/tests/results
UPDATING /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/_version.py
set /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/_version.py to '0.11.1'
running build_ext
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/_exponential_smoothers.c:617:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/regime_switching/_hamilton_filter.c:617:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/regime_switching/_hamilton_filter.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/regime_switching/_hamilton_filter.c:10729:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10729 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/regime_switching/_hamilton_filter.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/regime_switching/_hamilton_filter.c:10764:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10764 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/regime_switching/_hamilton_filter.c:10773:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10773 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/regime_switching/_hamilton_filter.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/regime_switching/_hamilton_filter.c:10807:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10807 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/regime_switching/_hamilton_filter.c:10814:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10814 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/regime_switching/_kim_smoother.c:617:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/regime_switching/_kim_smoother.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/regime_switching/_kim_smoother.c:9298:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
9298 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/regime_switching/_kim_smoother.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/regime_switching/_kim_smoother.c:9333:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
9333 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/regime_switching/_kim_smoother.c:9342:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
9342 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/regime_switching/_kim_smoother.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/regime_switching/_kim_smoother.c:9376:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
9376 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/regime_switching/_kim_smoother.c:9383:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
9383 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/innovations/_arma_innovations.c:618:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/innovations/_arma_innovations.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/innovations/_arma_innovations.c:16336:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16336 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/innovations/_arma_innovations.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/innovations/_arma_innovations.c:16371:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16371 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/innovations/_arma_innovations.c:16380:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16380 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/innovations/_arma_innovations.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/innovations/_arma_innovations.c:16414:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16414 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/innovations/_arma_innovations.c:16421:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16421 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/nonparametric/linbin.c:617:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/nonparametric/_smoothers_lowess.c:617:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/kalmanf/kalman_loglike.c:622:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/kalmanf/kalman_loglike.c: In function '__pyx_pf_11statsmodels_3tsa_7kalmanf_14kalman_loglike_kalman_filter_double':
statsmodels/tsa/kalmanf/kalman_loglike.c:3748:30: warning: comparison of integer expressions of different signedness: 'int' and 'unsigned int' [-Wsign-compare]
3748 | __pyx_t_19 = ((__pyx_v_i < __pyx_v_nobs) != 0);
| ^
statsmodels/tsa/kalmanf/kalman_loglike.c:4121:43: warning: comparison of integer expressions of different signedness: 'int' and 'unsigned int' [-Wsign-compare]
4121 | for (__pyx_t_15 = __pyx_v_i; __pyx_t_15 < __pyx_t_89; __pyx_t_15+=1) {
| ^
statsmodels/tsa/kalmanf/kalman_loglike.c: In function '__pyx_pf_11statsmodels_3tsa_7kalmanf_14kalman_loglike_2kalman_filter_complex':
statsmodels/tsa/kalmanf/kalman_loglike.c:5298:30: warning: comparison of integer expressions of different signedness: 'int' and 'unsigned int' [-Wsign-compare]
5298 | __pyx_t_19 = ((__pyx_v_i < __pyx_v_nobs) != 0);
| ^
statsmodels/tsa/kalmanf/kalman_loglike.c:5699:43: warning: comparison of integer expressions of different signedness: 'int' and 'unsigned int' [-Wsign-compare]
5699 | for (__pyx_t_15 = __pyx_v_i; __pyx_t_15 < __pyx_t_90; __pyx_t_15+=1) {
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_initialization.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_initialization.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/statespace/_initialization.c:16216:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16216 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_initialization.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/statespace/_initialization.c:16251:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16251 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_initialization.c:16260:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16260 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/statespace/_initialization.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/statespace/_initialization.c:16294:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16294 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_initialization.c:16301:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16301 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_representation.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_representation.c: In function '__pyx_f_11statsmodels_3tsa_10statespace_15_representation_11sStatespace_seek':
statsmodels/tsa/statespace/_representation.c:8734:28: warning: comparison of integer expressions of different signedness: 'unsigned int' and 'int' [-Wsign-compare]
8734 | __pyx_t_10 = ((__pyx_v_t >= __pyx_v_self->nobs) != 0);
| ^~
statsmodels/tsa/statespace/_representation.c: In function '__pyx_f_11statsmodels_3tsa_10statespace_15_representation_11dStatespace_seek':
statsmodels/tsa/statespace/_representation.c:19330:28: warning: comparison of integer expressions of different signedness: 'unsigned int' and 'int' [-Wsign-compare]
19330 | __pyx_t_10 = ((__pyx_v_t >= __pyx_v_self->nobs) != 0);
| ^~
statsmodels/tsa/statespace/_representation.c: In function '__pyx_f_11statsmodels_3tsa_10statespace_15_representation_11cStatespace_seek':
statsmodels/tsa/statespace/_representation.c:29934:28: warning: comparison of integer expressions of different signedness: 'unsigned int' and 'int' [-Wsign-compare]
29934 | __pyx_t_10 = ((__pyx_v_t >= __pyx_v_self->nobs) != 0);
| ^~
statsmodels/tsa/statespace/_representation.c: In function '__pyx_f_11statsmodels_3tsa_10statespace_15_representation_11zStatespace_seek':
statsmodels/tsa/statespace/_representation.c:40543:28: warning: comparison of integer expressions of different signedness: 'unsigned int' and 'int' [-Wsign-compare]
40543 | __pyx_t_10 = ((__pyx_v_t >= __pyx_v_self->nobs) != 0);
| ^~
statsmodels/tsa/statespace/_representation.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/statespace/_representation.c:48900:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
48900 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_representation.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/statespace/_representation.c:48935:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
48935 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_representation.c:48944:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
48944 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/statespace/_representation.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/statespace/_representation.c:48978:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
48978 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_representation.c:48985:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
48985 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_kalman_filter.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_kalman_filter.c: In function '__pyx_f_11statsmodels_3tsa_10statespace_14_kalman_filter_13sKalmanFilter_seek':
statsmodels/tsa/statespace/_kalman_filter.c:9706:28: warning: comparison of integer expressions of different signedness: 'unsigned int' and 'int' [-Wsign-compare]
9706 | __pyx_t_10 = ((__pyx_v_t >= __pyx_v_self->model->nobs) != 0);
| ^~
statsmodels/tsa/statespace/_kalman_filter.c: In function '__pyx_f_11statsmodels_3tsa_10statespace_14_kalman_filter_13dKalmanFilter_seek':
statsmodels/tsa/statespace/_kalman_filter.c:22910:28: warning: comparison of integer expressions of different signedness: 'unsigned int' and 'int' [-Wsign-compare]
22910 | __pyx_t_10 = ((__pyx_v_t >= __pyx_v_self->model->nobs) != 0);
| ^~
statsmodels/tsa/statespace/_kalman_filter.c: In function '__pyx_f_11statsmodels_3tsa_10statespace_14_kalman_filter_13cKalmanFilter_seek':
statsmodels/tsa/statespace/_kalman_filter.c:36151:28: warning: comparison of integer expressions of different signedness: 'unsigned int' and 'int' [-Wsign-compare]
36151 | __pyx_t_10 = ((__pyx_v_t >= __pyx_v_self->model->nobs) != 0);
| ^~
statsmodels/tsa/statespace/_kalman_filter.c: In function '__pyx_f_11statsmodels_3tsa_10statespace_14_kalman_filter_13zKalmanFilter_seek':
statsmodels/tsa/statespace/_kalman_filter.c:49422:28: warning: comparison of integer expressions of different signedness: 'unsigned int' and 'int' [-Wsign-compare]
49422 | __pyx_t_10 = ((__pyx_v_t >= __pyx_v_self->model->nobs) != 0);
| ^~
statsmodels/tsa/statespace/_kalman_filter.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/statespace/_kalman_filter.c:60056:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
60056 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_kalman_filter.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/statespace/_kalman_filter.c:60091:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
60091 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_kalman_filter.c:60100:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
60100 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/statespace/_kalman_filter.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/statespace/_kalman_filter.c:60134:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
60134 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_kalman_filter.c:60141:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
60141 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_filters/_conventional.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_filters/_conventional.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/statespace/_filters/_conventional.c:10172:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10172 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_filters/_conventional.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/statespace/_filters/_conventional.c:10207:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10207 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_filters/_conventional.c:10216:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10216 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/statespace/_filters/_conventional.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/statespace/_filters/_conventional.c:10250:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10250 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_filters/_conventional.c:10257:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10257 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_filters/_inversions.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_filters/_inversions.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/statespace/_filters/_inversions.c:15751:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
15751 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_filters/_inversions.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/statespace/_filters/_inversions.c:15786:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
15786 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_filters/_inversions.c:15795:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
15795 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/statespace/_filters/_inversions.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/statespace/_filters/_inversions.c:15829:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
15829 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_filters/_inversions.c:15836:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
15836 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_filters/_univariate.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_filters/_univariate.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/statespace/_filters/_univariate.c:14070:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
14070 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_filters/_univariate.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/statespace/_filters/_univariate.c:14105:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
14105 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_filters/_univariate.c:14114:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
14114 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/statespace/_filters/_univariate.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/statespace/_filters/_univariate.c:14148:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
14148 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_filters/_univariate.c:14155:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
14155 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_filters/_univariate_diffuse.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_filters/_univariate_diffuse.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/statespace/_filters/_univariate_diffuse.c:11246:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11246 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_filters/_univariate_diffuse.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/statespace/_filters/_univariate_diffuse.c:11281:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11281 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_filters/_univariate_diffuse.c:11290:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11290 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/statespace/_filters/_univariate_diffuse.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/statespace/_filters/_univariate_diffuse.c:11324:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11324 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_filters/_univariate_diffuse.c:11331:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11331 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_kalman_smoother.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_kalman_smoother.c: In function '__pyx_f_11statsmodels_3tsa_10statespace_16_kalman_smoother_15sKalmanSmoother_seek':
statsmodels/tsa/statespace/_kalman_smoother.c:7986:27: warning: comparison of integer expressions of different signedness: 'unsigned int' and 'int' [-Wsign-compare]
7986 | __pyx_t_7 = ((__pyx_v_t >= __pyx_v_self->model->nobs) != 0);
| ^~
statsmodels/tsa/statespace/_kalman_smoother.c: In function '__pyx_f_11statsmodels_3tsa_10statespace_16_kalman_smoother_15dKalmanSmoother_seek':
statsmodels/tsa/statespace/_kalman_smoother.c:14544:27: warning: comparison of integer expressions of different signedness: 'unsigned int' and 'int' [-Wsign-compare]
14544 | __pyx_t_7 = ((__pyx_v_t >= __pyx_v_self->model->nobs) != 0);
| ^~
statsmodels/tsa/statespace/_kalman_smoother.c: In function '__pyx_f_11statsmodels_3tsa_10statespace_16_kalman_smoother_15cKalmanSmoother_seek':
statsmodels/tsa/statespace/_kalman_smoother.c:21102:27: warning: comparison of integer expressions of different signedness: 'unsigned int' and 'int' [-Wsign-compare]
21102 | __pyx_t_7 = ((__pyx_v_t >= __pyx_v_self->model->nobs) != 0);
| ^~
statsmodels/tsa/statespace/_kalman_smoother.c: In function '__pyx_f_11statsmodels_3tsa_10statespace_16_kalman_smoother_15zKalmanSmoother_seek':
statsmodels/tsa/statespace/_kalman_smoother.c:27660:27: warning: comparison of integer expressions of different signedness: 'unsigned int' and 'int' [-Wsign-compare]
27660 | __pyx_t_7 = ((__pyx_v_t >= __pyx_v_self->model->nobs) != 0);
| ^~
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_smoothers/_alternative.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_smoothers/_alternative.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/statespace/_smoothers/_alternative.c:11420:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11420 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_alternative.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/statespace/_smoothers/_alternative.c:11455:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11455 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_alternative.c:11464:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11464 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/statespace/_smoothers/_alternative.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/statespace/_smoothers/_alternative.c:11498:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11498 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_alternative.c:11505:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11505 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_smoothers/_classical.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_smoothers/_classical.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/statespace/_smoothers/_classical.c:11204:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11204 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_classical.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/statespace/_smoothers/_classical.c:11239:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11239 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_classical.c:11248:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11248 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/statespace/_smoothers/_classical.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/statespace/_smoothers/_classical.c:11282:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11282 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_classical.c:11289:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11289 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_smoothers/_conventional.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_smoothers/_conventional.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/statespace/_smoothers/_conventional.c:11692:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11692 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_conventional.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/statespace/_smoothers/_conventional.c:11727:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11727 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_conventional.c:11736:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11736 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/statespace/_smoothers/_conventional.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/statespace/_smoothers/_conventional.c:11770:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11770 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_conventional.c:11777:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
11777 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_smoothers/_univariate.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_smoothers/_univariate.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/statespace/_smoothers/_univariate.c:10746:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10746 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_univariate.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/statespace/_smoothers/_univariate.c:10781:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10781 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_univariate.c:10790:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10790 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/statespace/_smoothers/_univariate.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/statespace/_smoothers/_univariate.c:10824:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10824 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_univariate.c:10831:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
10831 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.c:16792:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16792 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.c:16827:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16827 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.c:16836:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16836 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.c:16870:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16870 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.c:16877:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
16877 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_simulation_smoother.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
In file included from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1830,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /usr/lib/python3/dist-packages/numpy/core/include/numpy/arrayobject.h:4,
from statsmodels/tsa/statespace/_tools.c:620:
/usr/lib/python3/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
17 | #warning "Using deprecated NumPy API, disable it with " \
| ^~~~~~~
statsmodels/tsa/statespace/_tools.c: In function '__pyx_f_11statsmodels_3src_4math_zabs':
statsmodels/tsa/statespace/_tools.c:37111:52: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
37111 | __pyx_r = npy_cabs((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_tools.c: In function '__pyx_f_11statsmodels_3src_4math_zlog':
statsmodels/tsa/statespace/_tools.c:37146:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
37146 | __pyx_v_x = npy_clog((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_tools.c:37155:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
37155 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
statsmodels/tsa/statespace/_tools.c: In function '__pyx_f_11statsmodels_3src_4math_zexp':
statsmodels/tsa/statespace/_tools.c:37189:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
37189 | __pyx_v_x = npy_cexp((((npy_cdouble *)(&__pyx_v_z))[0]));
| ^
statsmodels/tsa/statespace/_tools.c:37196:54: warning: dereferencing type-punned pointer will break strict-aliasing rules [-Wstrict-aliasing]
37196 | __pyx_r = (((__pyx_t_double_complex *)(&__pyx_v_x))[0]);
| ^
At top level:
statsmodels/tsa/statespace/_tools.c:27003:12: warning: '__pyx_f_11statsmodels_3tsa_10statespace_6_tools__zselect2' defined but not used [-Wunused-function]
27003 | static int __pyx_f_11statsmodels_3tsa_10statespace_6_tools__zselect2(CYTHON_UNUSED __pyx_t_double_complex *__pyx_v_a, CYTHON_UNUSED __pyx_t_double_complex *__pyx_v_b) {
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
statsmodels/tsa/statespace/_tools.c:19255:12: warning: '__pyx_f_11statsmodels_3tsa_10statespace_6_tools__cselect2' defined but not used [-Wunused-function]
19255 | static int __pyx_f_11statsmodels_3tsa_10statespace_6_tools__cselect2(CYTHON_UNUSED __pyx_t_float_complex *__pyx_v_a, CYTHON_UNUSED __pyx_t_float_complex *__pyx_v_b) {
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
statsmodels/tsa/statespace/_tools.c:11659:12: warning: '__pyx_f_11statsmodels_3tsa_10statespace_6_tools__dselect1' defined but not used [-Wunused-function]
11659 | static int __pyx_f_11statsmodels_3tsa_10statespace_6_tools__dselect1(CYTHON_UNUSED __pyx_t_5numpy_float64_t *__pyx_v_a) {
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
statsmodels/tsa/statespace/_tools.c:4084:12: warning: '__pyx_f_11statsmodels_3tsa_10statespace_6_tools__sselect1' defined but not used [-Wunused-function]
4084 | static int __pyx_f_11statsmodels_3tsa_10statespace_6_tools__sselect1(CYTHON_UNUSED __pyx_t_5numpy_float32_t *__pyx_v_a) {
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
make[1]: Leaving directory '/<<PKGBUILDDIR>>'
debian/rules override_dh_auto_test
make[1]: Entering directory '/<<PKGBUILDDIR>>'
TEST_SUCCESS=true ; cd tools && for testpy3ver in `py3versions -vs` ; do \
for testpath in ../.pybuild/*${testpy3ver}*/*/statsmodels ; do \
PYTHONPATH=${testpath}/.. python${testpy3ver} -m pytest -v ${testpath} || TEST_SUCCESS=false ; \
rm -rf ${testpath}/.pytest_cache ; \
done ; done ; ${TEST_SUCCESS}
============================= test session starts ==============================
platform linux -- Python 3.8.2, pytest-4.6.9, py-1.8.1, pluggy-0.13.0 -- /usr/bin/python3.8
cachedir: .pytest_cache
rootdir: /<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels, inifile: setup.cfg
collecting ... collected 12988 items
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_fit_regularized_invalid_method PASSED [ 3%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_params PASSED [ 3%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_llf PASSED [ 3%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_conf_int PASSED [ 3%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_bse PASSED [ 3%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_aic PASSED [ 3%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_bic PASSED [ 3%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_t PASSED [ 3%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_init_keys PASSED [ 3%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_null PASSED [ 3%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_summary PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_fit_regularized SKIPPED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_fit_regularized_invalid_method PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_params PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_llf PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_conf_int PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_bse PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_aic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_bic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_t PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_fit_regularized PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_init_keys PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_null PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_summary PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_exposure PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_fit_regularized_invalid_method PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_params PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_llf PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_conf_int PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_bse PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_aic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_bic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_t PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_fit_regularized PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_init_keys PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_null PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_summary PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_names PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_fit_regularized_invalid_method PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedPoisson_predict::test_mean PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedPoisson_predict::test_var PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedPoisson_predict::test_predict_prob PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_params PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_llf PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_aic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_fit_regularized PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_init_keys PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_null PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_summary PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_bse PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_conf_int PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_bic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_t PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_minimize PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_fit_regularized_invalid_method PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson_predict::test_mean PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson_predict::test_var PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson_predict::test_predict_prob PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_llf PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_bse PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_aic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_t PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_init_keys PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_null PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_summary PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_params PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_conf_int PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_bic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_fit_regularized PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_minimize PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_fit_regularized_invalid_method PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict::test_mean PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict::test_var PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict::test_predict_prob PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict::test_predict_generic_zi PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict2::test_mean PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict2::test_zero_nonzero_mean PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_diagnostic.py::TestCountDiagnostic::test_count PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_diagnostic.py::TestCountDiagnostic::test_probs PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_fit_regularized_invalid_method PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_params PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_conf_int PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_zstat PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_pvalues PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_cov_params PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_llf PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_llnull PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_llr PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_llr_pvalue PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_normalized_cov_params XFAIL [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_bse PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_dof PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_aic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_bic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_predict_xb PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_loglikeobs PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_jac PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_pred_table PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_resid_dev PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_resid_generalized PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_resid_response PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_predict XFAIL [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_fit_regularized_invalid_method PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_params PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_conf_int PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_zstat PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_pvalues PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_cov_params PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_llf PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_llnull PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_llr PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_llr_pvalue PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_normalized_cov_params XFAIL [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_bse PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_dof PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_aic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_bic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_predict PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_predict_xb PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_loglikeobs PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_jac PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_pred_table PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_resid_dev PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_resid_generalized PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_resid_response PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_fit_regularized_invalid_method PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_params PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_conf_int PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_zstat PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_pvalues PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_cov_params PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_llf PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_llnull PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_llr PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_llr_pvalue PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_normalized_cov_params XFAIL [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_bse PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_dof PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_aic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_bic PASSED [ 4%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_predict PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_predict_xb PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_loglikeobs PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_jac PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_pred_table PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_resid_dev PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_resid_generalized PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_resid_response PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_fit_regularized_invalid_method PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_params PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_conf_int PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_zstat PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_pvalues PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_cov_params PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_llf PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_llnull PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_llr PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_llr_pvalue PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_normalized_cov_params XFAIL [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_bse PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_dof PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_aic PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_bic PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_predict PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_predict_xb PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_loglikeobs PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_jac PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_pred_table PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_resid_dev PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_resid_generalized PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_resid_response PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_fit_regularized_invalid_method PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_params PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_conf_int PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_zstat PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_pvalues PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_cov_params PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_llf PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_llnull PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_llr PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_llr_pvalue PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_normalized_cov_params XFAIL [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_bse PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_dof PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_aic PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_bic PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_predict PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_predict_xb PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_loglikeobs PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_jac PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_pred_table PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_resid_dev PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_resid_generalized PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_resid_response PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_fit_regularized_invalid_method PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_params PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_conf_int PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_zstat PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_pvalues PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_cov_params PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_llf PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_llnull PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_llr PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_llr_pvalue PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_normalized_cov_params XFAIL [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_bse PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_dof PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_aic PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_bic PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_predict PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_predict_xb PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_loglikeobs PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_jac PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_pred_table PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_resid_dev PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_resid_generalized PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_resid_response PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_fit_regularized_invalid_method PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_params PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_conf_int PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_zstat PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_pvalues PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_cov_params PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_llf PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_llnull PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_llr PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_llr_pvalue PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_normalized_cov_params XFAIL [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_bse PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_dof PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_aic PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_bic PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_predict PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_predict_xb PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_loglikeobs PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_jac PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_pred_table PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_resid_dev PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_resid_generalized PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_resid_response PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_fit_regularized_invalid_method PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_params PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_conf_int PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_zstat PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_pvalues PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_cov_params PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_llf PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_llnull PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_llr PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_llr_pvalue PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_normalized_cov_params XFAIL [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_bse PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_dof PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_aic PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_bic PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_predict PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_predict_xb PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_loglikeobs PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_jac PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_pred_table PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_resid_dev PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_resid_generalized PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_resid_response PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_fit_regularized_invalid_method PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_params PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_conf_int PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_zstat PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_pvalues PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_cov_params PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_llf PASSED [ 5%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_llnull PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_llr PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_llr_pvalue PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_normalized_cov_params XFAIL [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_bse PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_dof PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_aic PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_bic PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_predict PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_predict_xb PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_loglikeobs PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_jac PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_pred_table PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_resid_dev PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_resid_generalized PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_resid_response PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_fit_regularized_invalid_method PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_params PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_conf_int PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_zstat PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_pvalues PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_cov_params PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_llf PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_llnull PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_llr PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_llr_pvalue PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_normalized_cov_params XFAIL [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_bse PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_dof PASSED [ 6%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_normalized_cov_params XFAIL [ 6%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_jac PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_pred_table PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_resid_dev PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_resid_generalized PASSED [ 6%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dydxoverall PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dydxmean PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dydxmedian PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dydxzero PASSED [ 6%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dyexoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dyexmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dyexmedian PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dyexzero PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eydxoverall PASSED [ 7%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eydxmedian PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eydxzero PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eyexoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eyexmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eyexmedian PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eyexzero PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_dydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_dydxmean PASSED [ 7%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_count_dydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_count_dydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_count_dummy_dydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_count_dummy_dydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_resid_pearson PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_exog1 PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_exog2 PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_exog1 PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_exog2 PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dydxmedian PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dydxzero PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dyexoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dyexmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dyexmedian PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dyexzero PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eydxmedian PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eydxzero PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eyexoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eyexmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eyexmedian PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eyexzero PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_dydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_dydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_eydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_eydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_count_dydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_count_dydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_count_dummy_dydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_count_dummy_dydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_resid_pearson PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_exog1 PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_exog2 PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_exog1 PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_exog2 PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_fit_regularized_invalid_method PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_params PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_conf_int PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_zstat PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_pvalues PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_cov_params PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_llf PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_llnull PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_llr PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_llr_pvalue PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_normalized_cov_params XFAIL [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_bse PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dof PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_aic PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_bic PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_predict PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_predict_xb PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_loglikeobs PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_jac PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_pred_table PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_resid_dev PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_resid_generalized PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_resid_response PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dydxmedian PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dydxzero PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dyexoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dyexmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dyexmedian PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dyexzero PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eydxmedian PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eydxzero PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eyexoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eyexmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eyexmedian PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eyexzero PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dummy_dydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dummy_dydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dummy_eydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dummy_eydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_count_dydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_count_dydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_count_dummy_dydxoverall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_count_dummy_dydxmean PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_fit_regularized_invalid_method PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_params PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_conf_int PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_zstat PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_pvalues PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_llf PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_llnull PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_llr PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_llr_pvalue PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_normalized_cov_params XFAIL [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_bse PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_dof PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_aic PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_bic PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_predict PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_predict_xb PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_loglikeobs PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_jac PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_margeff_overall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_margeff_dummy_overall PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_resid PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_predict_prob PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_cov_params XFAIL [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_fit_regularized_invalid_method PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_cov_params SKIPPED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_llf PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_llnull PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_llr PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_llr_pvalue PASSED [ 7%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_normalized_cov_params XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_dof PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_aic PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_bic PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_loglikeobs PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_jac PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_pvalues XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_bse PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_params PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_alpha PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_conf_int PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_zstat PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_fittedvalues PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_predict PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_predict_xb PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_fit_regularized_invalid_method PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_cov_params SKIPPED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_llf PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_llnull PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_llr PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_llr_pvalue PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_normalized_cov_params XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_bse PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_dof PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_aic PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_bic PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_loglikeobs PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_jac PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_pvalues XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_zstat PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_lnalpha PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_params PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_conf_int PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_predict XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_predict_xb XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_fit_regularized_invalid_method PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_cov_params SKIPPED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_llf PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_llnull PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_llr PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_llr_pvalue PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_normalized_cov_params XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_dof PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_aic PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_bic PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_loglikeobs PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_jac PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_pvalues XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_bse PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_params PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_alpha PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_conf_int PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_zstat PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_fittedvalues PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_predict PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_predict_xb PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_fit_regularized_invalid_method PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_cov_params SKIPPED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_llf PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_llnull PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_llr PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_llr_pvalue PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_normalized_cov_params XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_bse PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_dof PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_aic PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_bic PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_loglikeobs PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_jac PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_pvalues XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_zstat PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_lnalpha PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_params PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_conf_int PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_predict XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_predict_xb XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_fit_regularized_invalid_method PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_cov_params SKIPPED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_llnull PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_llr_pvalue PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_normalized_cov_params XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_dof PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_loglikeobs PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_jac PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_pvalues XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_aic PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_bic PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_conf_int PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_fittedvalues PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_predict PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_params PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_predict_xb PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_zstat PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_llf PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_llr PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_bse PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_fit_regularized_invalid_method PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_params PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_conf_int PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_zstat PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_pvalues PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_llf PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_llnull PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_llr PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_llr_pvalue PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_normalized_cov_params XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_bse PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_dof PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_aic PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_bic PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_predict PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_predict_xb PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_loglikeobs PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_jac PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_margeff_overall PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_margeff_mean PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_margeff_dummy PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_j PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_k PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_endog_names PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_pred_table PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_resid PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_cov_params XFAIL [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_fit_regularized_invalid_method PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_params PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_conf_int PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_zstat PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_pvalues PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_llf PASSED [ 8%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_llnull PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_llr PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_llr_pvalue PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_normalized_cov_params XFAIL [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_bse PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_dof PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_aic PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_bic PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_predict PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_predict_xb PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_loglikeobs PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_jac PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_margeff_overall PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_margeff_mean PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_margeff_dummy PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_j PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_k PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_endog_names PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_pred_table PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_resid PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_cov_params XFAIL [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_perfect_prediction PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_poisson_predict PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_poisson_newton PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_issue_339 PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_issue_341 PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_iscount PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_isdummy PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_non_binary PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_mnlogit_factor PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_mnlogit_factor_categorical PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_formula_missing_exposure PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_predict_with_exposure PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_binary_pred_table_zeros PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_bse PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_params PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_alpha PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_conf_int PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_aic PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_bic PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_df PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_llf PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_wald PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_t PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_bse PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_params PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_alpha PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_conf_int PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_aic PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_bic PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_df PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_llf PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_llf PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_score PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_hessian PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_t PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_fit_regularized PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_init_kwds PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_basic PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_newton PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_mean_var PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_predict_prob PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_fit_regularized_invalid_method PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_cov_params SKIPPED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_llf PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_llnull PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_llr PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_llr_pvalue PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_normalized_cov_params XFAIL [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_dof PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_aic PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_bic PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_loglikeobs PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_jac PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_pvalues XFAIL [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_bse PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_params PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_alpha PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_conf_int PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_zstat PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_fittedvalues PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_predict PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_predict_xb PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_fit_regularized_invalid_method PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_cov_params SKIPPED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_llf PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_llnull PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_llr PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_llr_pvalue PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_normalized_cov_params XFAIL [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_bse PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_dof PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_aic PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_bic PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_loglikeobs PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_jac PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_pvalues XFAIL [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_zstat PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_lnalpha PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_params PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_conf_int PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_predict PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_predict_xb PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_fit_regularized_invalid_method PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_cov_params SKIPPED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_llf PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_llnull PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_llr PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_llr_pvalue PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_normalized_cov_params XFAIL [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_dof PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_aic PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_bic PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_loglikeobs PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_jac PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_pvalues XFAIL [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_bse PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_params PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_alpha PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_conf_int PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_zstat PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_fittedvalues PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_predict PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_predict_xb PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_fit_regularized_invalid_method PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_cov_params SKIPPED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_llnull PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_llr_pvalue PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_normalized_cov_params XFAIL [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_dof PASSED [ 9%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_loglikeobs PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_jac PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_pvalues XFAIL [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_bse PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_aic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_bic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_llf PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_llr PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_zstat PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_lnalpha PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_params PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_conf_int PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_predict PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_predict_xb PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_init_kwds PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_params PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_cov_params PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_df PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_t_test PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_f_test PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_bad_r_matrix PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPPredictProb::test_predict_prob_p1 PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPPredictProb::test_predict_prob_p2 PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNull::test_llnull PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Null::test_llnull PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Null::test_llnull PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNBP2Null::test_llnull PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNBP2Null::test_start_null PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNBP1Null::test_llnull PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNBP1Null::test_start_null PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoissonNull::test_llnull PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_null_options PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_optim_kwds_prelim PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_unchanging_degrees_of_freedom PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_mnlogit_float_name PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_cov_confint_pandas PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_t_test PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_margins.py::TestPoissonMargin::test_margins_table PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_margins.py::TestPoissonMarginDummy::test_margins_table PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_margins.py::TestNegBinMargin::test_margins_table PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_margins.py::TestNegBinMarginDummy::test_margins_table PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_margins.py::TestNegBinPMargin::test_margins_table PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonClu::test_basic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonClu::test_oth PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonClu::test_ttest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonClu::test_waldtest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluGeneric::test_basic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluGeneric::test_oth PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluGeneric::test_ttest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluGeneric::test_waldtest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Generic::test_basic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Generic::test_oth PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Generic::test_ttest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Generic::test_waldtest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluFit::test_basic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluFit::test_oth PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluFit::test_ttest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluFit::test_waldtest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluFit::test_basic_inference PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Fit::test_basic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Fit::test_oth PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Fit::test_ttest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Fit::test_waldtest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1FitExposure::test_basic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1FitExposure::test_oth PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1FitExposure::test_ttest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1FitExposure::test_waldtest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposure::test_basic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposure::test_oth PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposure::test_ttest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposure::test_waldtest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposureGeneric::test_basic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposureGeneric::test_oth PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposureGeneric::test_ttest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluExposureGeneric::test_waldtest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonClu::test_basic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonClu::test_oth PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonClu::test_ttest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonClu::test_waldtest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluGeneric::test_basic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluGeneric::test_oth PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluGeneric::test_ttest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluGeneric::test_waldtest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Generic::test_basic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Generic::test_oth PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Generic::test_ttest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Generic::test_waldtest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluFit::test_basic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluFit::test_oth PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluFit::test_ttest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonCluFit::test_waldtest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Fit::test_basic PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Fit::test_oth PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Fit::test_ttest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestGLMPoissonHC1Fit::test_waldtest PASSED [ 10%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestNegbinClu::test_basic PASSED [ 10%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm.py::TestWtdGlmGaussian::test_fittedvalues PASSED [ 16%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm.py::TestRegularized::test_regularized PASSED [ 17%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm.py::test_poisson_deviance PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm.py::test_non_invertible_hessian_fails_summary PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonPlain::test_basic PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonPlain::test_residuals PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonPlain::test_compare_optimizers PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonPlain::test_pearson_chi2 PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonFwNr::test_basic PASSED [ 17%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonFwNr::test_compare_optimizers PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonFwNr::test_pearson_chi2 PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwNr::test_basic PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwNr::test_residuals PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwNr::test_compare_optimizers PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwNr::test_pearson_chi2 PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonPwNr::test_residuals PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonPwNr::test_pearson_chi2 PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonPwNr::test_basic XFAIL [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonPwNr::test_compare_optimizers XFAIL [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonFwHC::test_basic PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonFwHC::test_residuals PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonFwHC::test_compare_optimizers PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonFwHC::test_pearson_chi2 PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwHC::test_basic PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwHC::test_residuals PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwHC::test_compare_optimizers PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonAwHC::test_pearson_chi2 PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonFwClu::test_basic PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonFwClu::test_residuals PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonFwClu::test_compare_optimizers PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmPoissonFwClu::test_pearson_chi2 PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmTweedieAwNr::test_basic PASSED [ 17%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmTweedieAwNr::test_pearson_chi2 PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGammaAwNr::test_basic PASSED [ 17%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGammaAwNr::test_r_llf PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianAwNr::test_basic PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianAwNr::test_residuals PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianAwNr::test_compare_optimizers PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianAwNr::test_pearson_chi2 PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianAwNr::test_r_llf PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::test_wtd_gradient_irls PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestRepeatedvsAggregated::test_basic PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestRepeatedvsAggregated::test_residuals PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestRepeatedvsAggregated::test_compare_optimizers PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestRepeatedvsAggregated::test_pearson_chi2 PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestRepeatedvsAverage::test_basic PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestRepeatedvsAverage::test_residuals PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestRepeatedvsAverage::test_compare_optimizers PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestRepeatedvsAverage::test_pearson_chi2 PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestTweedieRepeatedvsAggregated::test_basic PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestTweedieRepeatedvsAggregated::test_residuals PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestTweedieRepeatedvsAggregated::test_compare_optimizers PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestTweedieRepeatedvsAggregated::test_pearson_chi2 PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestTweedieRepeatedvsAverage::test_basic PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestTweedieRepeatedvsAverage::test_residuals PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestTweedieRepeatedvsAverage::test_compare_optimizers PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestTweedieRepeatedvsAverage::test_pearson_chi2 PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsAverage::test_basic PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsAverage::test_residuals PASSED [ 17%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsAverage::test_compare_optimizers PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsAverage::test_pearson_chi2 PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsDuplicated::test_basic PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsDuplicated::test_residuals PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsDuplicated::test_compare_optimizers PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsDuplicated::test_pearson_chi2 PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::test_warnings_raised PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::test_weights_different_formats[list] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::test_weights_different_formats[ndarray] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::test_weights_different_formats[Series] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomialVsVarWeights::test_basic PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomialVsVarWeights::test_residuals PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomialVsVarWeights::test_compare_optimizers PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomialVsVarWeights::test_pearson_chi2 PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianWLS::test_basic PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianWLS::test_residuals PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianWLS::test_compare_optimizers PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianWLS::test_pearson_chi2 PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::test_incompatible_input PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::test_poisson_residuals PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct0-fam0] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct0-fam1] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct0-fam2] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct1-fam0] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct1-fam1] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct1-fam2] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct2-fam0] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct2-fam1] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct2-fam2] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct0-fam0] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct0-fam1] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct0-fam2] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct1-fam0] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct1-fam1] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct1-fam2] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct2-fam0] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct2-fam1] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct2-fam2] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_formula[cov_struct0] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_formula[cov_struct1] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_formula[cov_struct2] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTest::test_wald_score PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTest::test_dispersion PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTestDispersed::test_wald_score PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTestDispersed::test_dispersion PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTestPoisson::test_dispersion PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTestPoisson::test_wald_score PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTestPoissonDispersed::test_dispersion PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTestPoissonDispersed::test_wald_score PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_agreement.py::test_mean_diff_plot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_violinplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_violinplot_bw_factor PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_beanplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_beanplot_jitter PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_beanplot_side_right PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_beanplot_side_left PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_beanplot_legend_text PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_correlation.py::test_plot_corr PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_correlation.py::test_plot_corr_grid PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_dotplot.py::test_all PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plot_both PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plot_rainbow PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plot_pandas[str] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plot_pandas[int] PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_formatting PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_formatting_errors PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plottype PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_recode_series PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_basic PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_basic_brute PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_plot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_alpha PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_multiple_alpha PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_threshold PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_bw PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_ncomp PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_banddepth_BD2 PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_banddepth_MBD PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_fboxplot_rainbowplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_qqplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_ppplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_probplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_qqplot_other_array PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_ppplot_other_array PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_probplot_other_array XFAIL [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_qqplot_other_prbplt PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_ppplot_other_prbplt PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_probplot_other_prbplt XFAIL [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_qqplot_custom_labels PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_ppplot_custom_labels PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_probplot_custom_labels PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_qqplot_pltkwargs PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_ppplot_pltkwargs PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_probplot_pltkwargs PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongely::test_fit_params PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_qqplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_ppplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_probplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_qqplot_other_array PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_ppplot_other_array PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_probplot_other_array XFAIL [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_qqplot_other_prbplt PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_ppplot_other_prbplt PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_probplot_other_prbplt XFAIL [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_qqplot_custom_labels PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_ppplot_custom_labels PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_probplot_custom_labels PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_qqplot_pltkwargs PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_ppplot_pltkwargs PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_probplot_pltkwargs PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_fit_params PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot_other_array PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot_other_array PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_other_array XFAIL [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot_other_prbplt PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot_other_prbplt PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_other_prbplt XFAIL [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot_custom_labels PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot_custom_labels PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_custom_labels PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot_pltkwargs PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot_pltkwargs PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_pltkwargs PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_fit_params PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_qqplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_ppplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_probplot PASSED [ 18%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_qqplot_other_array PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_ppplot_other_array PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_probplot_other_array XFAIL [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_qqplot_other_prbplt PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_ppplot_other_prbplt PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_probplot_other_prbplt XFAIL [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_qqplot_custom_labels PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_ppplot_custom_labels PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_probplot_custom_labels PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_qqplot_pltkwargs PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_ppplot_pltkwargs PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_probplot_pltkwargs PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_fit_params PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_loc_set PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScale::test_scale_set PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestCompareSamplesDifferentSize::test_qqplot PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestCompareSamplesDifferentSize::test_ppplot PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_qqplot PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_ppplot PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_probplot PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_qqplot_other_array PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_ppplot_other_array PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_probplot_other_array XFAIL [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_qqplot_other_prbplt PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_ppplot_other_prbplt PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_probplot_other_prbplt XFAIL [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_qqplot_custom_labels PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_ppplot_custom_labels PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_probplot_custom_labels PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_qqplot_pltkwargs PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_ppplot_pltkwargs PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_probplot_pltkwargs PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_fit_params PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_loc_set PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_scale_set PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_loc_set_in_dist PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_scale_set_in_dist PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestTopLevel::test_qqplot PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestTopLevel::test_qqplot_pltkwargs PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestTopLevel::test_qqplot_2samples_ProbPlotObjects PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestTopLevel::test_qqplot_2samples_arrays PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_invalid_dist_config PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_data_conversion PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_mosaic_simple PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_mosaic PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_mosaic_very_complex PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_axes_labeling PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_mosaic_empty_cells PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_recursive_split PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test__reduce_dict PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test__key_splitting PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_proportion_normalization PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_false_split PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_rect_pure_split PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_rect_deformed_split PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_gap_split PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_default_arg_index PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_missing_category PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPlot::test_plot_fit PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPlot::test_plot_oth PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPlot::test_plot_influence PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPlot::test_plot_leverage_resid2 PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPlotPandas::test_plot_fit PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPlotPandas::test_plot_oth PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPlotPandas::test_plot_influence PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPlotPandas::test_plot_leverage_resid2 PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPlotFormula::test_plot_fit PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPlotFormula::test_plot_oth PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPlotFormula::test_plot_influence PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPlotFormula::test_plot_leverage_resid2 PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPlotFormula::test_one_column_exog PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestABLine::test_abline_model PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestABLine::test_abline_model_ax PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestABLine::test_abline_ab PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestABLine::test_abline_ab_ax PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestABLine::test_abline_remove PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestABLinePandas::test_abline_model PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestABLinePandas::test_abline_model_ax PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestABLinePandas::test_abline_ab PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestABLinePandas::test_abline_ab_ax PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestABLinePandas::test_abline_remove PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestAddedVariablePlot::test_added_variable_poisson PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestPartialResidualPlot::test_partial_residual_poisson PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_regressionplots.py::TestCERESPlot::test_ceres_poisson PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_tsaplots.py::test_plot_acf PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_tsaplots.py::test_plot_acf_irregular PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_tsaplots.py::test_plot_pacf PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_tsaplots.py::test_plot_pacf_kwargs PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_tsaplots.py::test_plot_acf_kwargs PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_tsaplots.py::test_plot_acf_missing PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_tsaplots.py::test_plot_pacf_irregular PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_tsaplots.py::test_plot_month PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_tsaplots.py::test_plot_quarter PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/graphics/tests/test_tsaplots.py::test_seasonal_plot PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_bayes_mi.py::test_pat PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_bayes_mi.py::test_2x2 PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_bayes_mi.py::test_MI PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_bayes_mi.py::test_MI_stat PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_bayes_mi.py::test_mi_formula PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICEData::test_default PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICEData::test_settingwithcopywarning PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICEData::test_next_sample PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICEData::test_pertmeth PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICEData::test_phreg PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICEData::test_set_imputer PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICEData::test_plot_missing_pattern PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICEData::test_plot_bivariate PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICEData::test_fit_obs PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICEData::test_plot_imputed_hist PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICE::test_MICE PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICE::test_MICE1 PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICE::test_MICE1_regularized PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICE::test_MICE2 PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::TestMICE::test_combine PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_mice.py::test_micedata_miss1 PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_ros.py::Test__ros_sort::test_baseline PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_ros.py::Test__ros_sort::test_censored_greater_than_max PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_ros.py::Test_cohn_numbers::test_baseline PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_ros.py::Test_cohn_numbers::test_no_NDs PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_ros.py::Test__detection_limit_index::test_empty PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_ros.py::Test__detection_limit_index::test_populated PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_ros.py::Test__detection_limit_index::test_out_of_bounds PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_ros.py::test__ros_group_rank PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_ros.py::Test__ros_plot_pos::test_uncensored_1 PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_ros.py::Test__ros_plot_pos::test_uncensored_2 PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_ros.py::Test__ros_plot_pos::test_censored_1 PASSED [ 19%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/imputation/tests/test_ros.py::Test__ros_plot_pos::test_censored_2 PASSED [ 19%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_bandwidths.py::TestGaussian::test_calculate_normal_reference_constant PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_bandwidths.py::TestBiweight::test_calculate_normal_reference_constant PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_bandwidths.py::TestTriweight::test_calculate_normal_reference_constant PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_bandwidths.py::TestAllBandwidthZero::test_bandwidth_zero PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_bandwidths.py::TestAnyBandwidthZero::test_bandwidth_zero PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEExceptions::test_check_is_fit_exception PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEExceptions::test_non_weighted_fft_exception PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEExceptions::test_wrong_weight_length_exception PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEExceptions::test_non_gaussian_fft_exception PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_density PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_evaluate PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_support_gridded PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_cdf_gridded PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_sf_gridded PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_icdf_gridded PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEEpanechnikov::test_density PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEEpanechnikov::test_evaluate PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDETriangular::test_density PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDETriangular::test_evaluate PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEBiweight::test_density PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEBiweight::test_evaluate PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKdeWeights::test_density PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKdeWeights::test_evaluate PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussFFT::test_density PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussFFT::test_evaluate PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWGauss::test_density XFAIL [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWGauss::test_evaluate PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWGauss::test_compare PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWGauss::test_kernel_constants PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWEpa::test_density XFAIL [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWEpa::test_evaluate PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWEpa::test_compare PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWEpa::test_kernel_constants PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWTri::test_density XFAIL [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWTri::test_evaluate PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWTri::test_compare PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWTri::test_kernel_constants PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWBiw::test_density XFAIL [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWBiw::test_evaluate PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWBiw::test_compare PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWBiw::test_kernel_constants PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos::test_density XFAIL [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos::test_evaluate SKIPPED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos::test_compare PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos::test_kernel_constants PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos2::test_density XFAIL [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos2::test_evaluate PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos2::test_compare PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos2::test_kernel_constants PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestNormConstant::test_norm_constant_calculation PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEUnivariate::test_pdf_non_fft PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEUnivariate::test_weighted_pdf_non_fft PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEUnivariate::test_all_samples_same_location_bw PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEUnivariate::test_int PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_pdf_mixeddata_CV_LS PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_pdf_mixeddata_LS_vs_ML PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_pdf_mixeddata_CV_ML PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_pdf_continuous PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_pdf_ordered PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_unordered_CV_LS PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_continuous_cdf PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_mixeddata_cdf PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_continuous_cvls_efficient PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_continuous_cvml_efficient PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_efficient_notrandom PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_efficient_user_specified_bw PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_mixeddata_CV_LS PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_continuous_CV_ML PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_unordered_CV_LS PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_pdf_continuous PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_pdf_mixeddata PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_continuous_normal_ref PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_continuous_cdf PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_mixeddata_cdf PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_continuous_cvml_efficient PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_efficient_user_specified_bw PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_ordered_lc_cvls PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuousdata_lc_cvls PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuousdata_ll_cvls PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuous_mfx_ll_cvls PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_mixed_mfx_ll_cvls PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_mfx_nonlinear_ll_cvls XFAIL [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuous_cvls_efficient PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_censored_ll_cvls PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuous_lc_aic PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_significance_continuous PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_significance_discrete PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_user_specified_kernel PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_censored_user_specified_kernel PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_efficient_user_specificed_bw PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_censored_efficient_user_specificed_bw PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::test_invalid_bw PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::test_invalid_kernel PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestEpan::test_smoothconf PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestEpan::test_smoothconf_data PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestGau::test_smoothconf PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestGau::test_smoothconf_data PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestUniform::test_smoothconf PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestUniform::test_smoothconf_data PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestTriangular::test_smoothconf PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestTriangular::test_smoothconf_data PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestCosine::test_smoothconf_data PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestCosine::test_smoothconf XFAIL [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestBiweight::test_smoothconf PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestBiweight::test_smoothconf_data PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_import PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_flat PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_range PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_simple PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_iter_0 PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_iter_0_3 PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_frac_2_3 PASSED [ 21%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_frac_1_5 PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_delta_0 PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_delta_rdef PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_delta_1 PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_options PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::test_returns_inputs PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_cov.py::test_HC_use PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_dimred.py::test_poisson PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_dimred.py::test_sir_regularized_numdiff PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_dimred.py::test_sir_regularized_1d PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_dimred.py::test_sir_regularized_2d PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_dimred.py::test_covreduce PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_glsar_gretl.py::TestGLSARGretl::test_all PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_glsar_gretl.py::test_GLSARlag PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_glsar_stata.py::TestGLSARCorc::test_params_table PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_glsar_stata.py::TestGLSARCorc::test_predicted PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_glsar_stata.py::TestGLSARCorc::test_rho PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_glsar_stata.py::TestGLSARCorc::test_glsar_arima PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_glsar_stata.py::TestGLSARCorc::test_glsar_iter0 PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_compare_numdiff[False-False-False] PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_compare_numdiff[False-False-True] PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_compare_numdiff[False-True-False] PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_compare_numdiff[False-True-True] PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_compare_numdiff[True-False-False] PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_compare_numdiff[True-False-True] PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_compare_numdiff[True-True-False] PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_compare_numdiff[True-True-True] PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_default_re PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_history PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_profile_inference PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_vcomp_1 PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_vcomp_2 PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_vcomp_3 PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_sparse PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_dietox PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_dietox_slopes PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_pastes_vcomp PASSED [ 22%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_lme.py::TestMixedLM::test_vcomp_formula PASSED [ 22%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmAndrewsHuber::test_confidenceintervals PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmAndrewsHuber::test_scale PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmAndrewsHuber::test_weights PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmAndrewsHuber::test_residuals PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmAndrewsHuber::test_degrees PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmAndrewsHuber::test_bcov_unscaled SKIPPED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmAndrewsHuber::test_bcov_scaled PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmAndrewsHuber::test_tvalues SKIPPED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmAndrewsHuber::test_tpvalues PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmAndrewsHuber::test_summary PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmAndrewsHuber::test_summary2 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmAndrewsHuber::test_chisq PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmAndrewsHuber::test_predict PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_params PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_standarderrors PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_confidenceintervals SKIPPED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_scale PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_weights PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_residuals PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_degrees PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_bcov_unscaled PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_bcov_scaled PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_tvalues PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_tpvalues PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_missing PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_rlm_start_values PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_rlm_start_values_errors PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[AndrewWave] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[AndrewWave] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[LeastSquares] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[LeastSquares] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[HuberT] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[HuberT] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[TrimmedMean] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[TrimmedMean] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[TukeyBiweight] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[TukeyBiweight] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[Hampel] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[Hampel] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[RamsayE] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[RamsayE] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_alt_criterion[weights] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_alt_criterion[coefs] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_alt_criterion[sresid] PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_bad_criterion PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_mean PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_median PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_mad PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_huber_scale PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_huber_location PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_huber_huberT PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_huber_Hampel PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMad::test_mad PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMad::test_mad_empty PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMad::test_mad_center PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMadAxes::test_axis0 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMadAxes::test_axis1 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMadAxes::test_axis2 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMadAxes::test_axisneg1 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestHuber::test_huber_result_shape PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestHuberAxes::test_default PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestHuberAxes::test_axis1 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestHuberAxes::test_axis2 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestHuberAxes::test_axisneg1 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_extras.py::test_skewnorm PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_extras.py::test_skewt PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_gof_new.py::test_loop_vectorized_batch_equivalence PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::Test_MVN_MVT_prob::test_mvn_mvt_1 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::Test_MVN_MVT_prob::test_mvn_mvt_2 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::Test_MVN_MVT_prob::test_mvn_mvt_3 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::Test_MVN_MVT_prob::test_mvn_mvt_4 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::Test_MVN_MVT_prob::test_mvn_mvt_5 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::TestMVDistributions::test_mvn_pdf PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::TestMVDistributions::test_mvt_pdf PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_norm_expan.py::TestExpandNormMom::test_dist1 PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_norm_expan.py::TestExpandNormMom::test_cdf_ppf_roundtrip PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_norm_expan.py::TestExpandNormMom::test_pdf PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_norm_expan.py::TestExpandNormMom::test_mvsk PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_norm_expan.py::TestExpandNormSample::test_ks PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_norm_expan.py::TestExpandNormSample::test_mvsk PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_transf.py::Test_Transf2::test_equivalent PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/distributions/tests/test_transf.py::Test_Transf2::test_equivalent_negsq PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_kernel_extras.py::TestSemiLinear::test_basic PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother1::test_predict PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother1::test_coef PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother1::test_df PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother2::test_predict PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother2::test_coef PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother2::test_df PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother3::test_predict PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother3::test_coef PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother3::test_df PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/panel/tests/test_random_panel.py::test_short_panel PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::test_iv2sls_r PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::test_ivgmm0_r PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::test_ivgmm1_stata PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMOLS::test_basic PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMOLS::test_other XFAIL [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_basic PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_other PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_hypothesis PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_summary PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_use_t PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_basic PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_other PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_hypothesis PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_summary PASSED [ 31%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_use_t PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_other PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_hypothesis PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_use_t PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_hypothesis PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_use_t PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_bse_other PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_other XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_hypothesis PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_use_t PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_other XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_hypothesis PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_use_t PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_other XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_bse_other PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_hypothesis PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_use_t PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_other XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_hypothesis PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_use_t PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_other XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_hypothesis PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_use_t PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_other XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_score PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_hypothesis PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_use_t PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_other XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt2::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_other PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_hypothesis PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_hausman PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_input_dimensions PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::test_noconstant PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::test_gmm_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddOnestep::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddOnestep::test_other PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddOnestep::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddTwostep::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddTwostep::test_other PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddTwostep::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultOnestep::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultOnestep::test_other PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultOnestep::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostep::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostep::test_other PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostep::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepDefault::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepDefault::test_other PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepDefault::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepCenter::test_basic PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepCenter::test_other PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepCenter::test_summary PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepCenter::test_more PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/stats/tests/test_multicomp.py::test_tukey_pvalues PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestAdditiveModel::test_predict PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestAdditiveModel::test_params PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestAdditiveModel::test_df XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestAdditiveModel::test_fitted PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMPoisson::test_predict PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMPoisson::test_fitted XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMPoisson::test_params PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMPoisson::test_df XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMPoisson::test_mu PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMPoisson::test_prediction PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMBinomial::test_predict PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMBinomial::test_fitted XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMBinomial::test_params PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMBinomial::test_df XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMBinomial::test_mu PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMBinomial::test_prediction PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_predict XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_fitted XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_params XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_df XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_mu XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_prediction XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGamma::test_predict PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGamma::test_fitted XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGamma::test_params PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGamma::test_df XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGamma::test_mu PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGamma::test_prediction PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMNegativeBinomial::test_predict XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMNegativeBinomial::test_params XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMNegativeBinomial::test_mu XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMNegativeBinomial::test_prediction XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMNegativeBinomial::test_fitted XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMNegativeBinomial::test_df XFAIL [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_pca.py::test_pca_princomp PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_pca.py::test_pca_svd PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_predict_functional.py::TestPredFunc::test_formula PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_predict_functional.py::TestPredFunc::test_lm_contrast PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_predict_functional.py::TestPredFunc::test_glm_formula_contrast PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_predict_functional.py::TestPredFunc::test_scb PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_predict_functional.py::TestPredFunc::test_glm_formula PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/tests/test_predict_functional.py::TestPredFunc::test_noformula_prediction PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_scalar PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_vector PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_invalid_parameters PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_handful_to_tbl PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_all_to_tbl SKIPPED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_handful_to_ch PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_10000_to_ch PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_scalar PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_vector PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_v_equal_one PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_invalid_parameters PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_handful_to_known_values PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_100_random_values PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnovaLM::test_results PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnovaLMNoconstant::test_results PASSED [ 32%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnovaLMCompare::test_results PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnovaLMCompareNoconstant::test_results PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova2::test_results PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova2Noconstant::test_results PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova2HC0::test_results PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova2HC1::test_results PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova2HC2::test_results PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova2HC3::test_results PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova3::test_results PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova3HC0::test_results PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova3HC1::test_results PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova3HC2::test_results PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova3HC3::test_results PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_single_factor_repeated_measures_anova PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_two_factors_repeated_measures_anova PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_three_factors_repeated_measures_anova PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_invalid_factor_name PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_collinearity PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_unbalanced_data PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_aggregation PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_aggregation_one_subject_duplicated PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_aggregate_func PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_aggregate_func_mean PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_aggregate_compare_with_ezANOVA PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_homogeneity PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_SquareTable_from_data PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_SquareTable_nonsquare PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_cumulative_odds PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_local_odds PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_shifting PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_stratified_table_cube PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_resids PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_ordinal_association PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_chi2_association PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_symmetry PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_mcnemar PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_from_data_stratified PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_from_data_2x2 PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_cochranq PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified1::test_oddsratio_pooled PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified1::test_logodds_pooled PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified1::test_null_odds PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified1::test_oddsratio_pooled_confint PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified1::test_logodds_pooled_confint PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified1::test_equal_odds PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified1::test_pandas PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified1::test_from_data PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_oddsratio_pooled PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_logodds_pooled PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_null_odds PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_oddsratio_pooled_confint PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_logodds_pooled_confint PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_equal_odds PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_pandas PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified2::test_from_data PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified3::test_oddsratio_pooled PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified3::test_logodds_pooled PASSED [ 33%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::TestStratified3::test_null_odds PASSED [ 33%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_decorators.py::test_deprecated_alias[None-0.11-FutureWarning] PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_decorators.py::test_deprecated_alias[None-0.11-UserWarning] PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_docstring.py::test_remove_parameter PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_docstring.py::test_insert_parameters PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_docstring.py::test_set_unknown PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_docstring.py::test_replace_block PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_docstring.py::test_repeat PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_docstring.py::test_bad PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_docstring.py::test_empty_ds PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_docstring.py::test_yield_return PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_docstring.py::test_multiple_sig PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_eval_measures.py::test_eval_measures PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_eval_measures.py::test_ic_equivalence[aic-aic_sigma] PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_eval_measures.py::test_ic_equivalence[aicc-aicc_sigma] PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_eval_measures.py::test_ic_equivalence[bic-bic_sigma] PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_eval_measures.py::test_ic_equivalence[hqic-hqic_sigma] PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_eval_measures.py::test_ic PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_eval_measures.py::test_iqr_axis PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestMultiIndexGrouping::test_reindex PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestMultiIndexGrouping::test_count_categories PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestMultiIndexGrouping::test_sort PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestMultiIndexGrouping::test_transform_dataframe PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestMultiIndexGrouping::test_transform_array PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestMultiIndexGrouping::test_transform_slices PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestMultiIndexGrouping::test_dummies_groups PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestMultiIndexGrouping::test_dummy_sparse PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestIndexGrouping::test_reindex PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestIndexGrouping::test_count_categories PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestIndexGrouping::test_sort PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestIndexGrouping::test_transform_dataframe PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestIndexGrouping::test_transform_array PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestIndexGrouping::test_transform_slices PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestIndexGrouping::test_dummies_groups PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::TestIndexGrouping::test_dummy_sparse PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::test_init_api PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::test_combine_indices PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::test_group_sums PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::test_group_class PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_grouputils.py::test_dummy_sparse PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_linalg.py::test_stationary_solve_1d PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_linalg.py::test_stationary_solve_2d PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestGradMNLogit::test_score PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestGradMNLogit::test_hess PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestGradLogit::test_score PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestGradLogit::test_hess PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestDerivativeFun::test_grad_fun1_fd PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestDerivativeFun::test_grad_fun1_fdc PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestDerivativeFun::test_grad_fun1_cs PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestDerivativeFun::test_hess_fun1_fd PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestDerivativeFun::test_hess_fun1_cs PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestDerivativeFun2::test_grad_fun1_fd PASSED [ 41%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestDerivativeFun2::test_grad_fun1_cs PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestDerivativeFun2::test_hess_fun1_fd PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestDerivativeFun2::test_hess_fun1_cs PASSED [ 41%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestDerivativeFun1::test_grad_fun1_fdc PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestDerivativeFun1::test_grad_fun1_cs PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestDerivativeFun1::test_hess_fun1_fd PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::TestDerivativeFun1::test_hess_fun1_cs PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_numdiff.py::test_dtypes PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_parallel.py::test_parallel PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_rootfinding.py::test_brentq_expanding PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_sequences.py::test_discrepancy PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_sequences.py::test_van_der_corput PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_sequences.py::test_primes PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_sequences.py::test_halton PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_testing.py::test_bad_table PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_testing.py::test_holder PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestTools::test_add_constant_list PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestTools::test_add_constant_1d PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestTools::test_add_constant_has_constant1d PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestTools::test_add_constant_has_constant2d PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestTools::test_add_constant_recarray PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestTools::test_add_constant_series PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestTools::test_add_constant_dataframe PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestTools::test_add_constant_zeros PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestTools::test_recipr PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestTools::test_recipr0 PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestTools::test_extendedpinv PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestTools::test_extendedpinv_singular PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestTools::test_fullrank PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::test_estimable PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_array2d PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_array1d PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_array1d_col_error PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_array2d_drop PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_array1d_drop PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_recarray2d PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_recarray2d_error PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_recarray2dint PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_recarray1d PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_recarray1d_drop PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_recarray2d_drop PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_structarray2d PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_structarray2dint PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_structarray1d PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_structarray2d_drop PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_structarray1d_drop PASSED [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_arraylike2d XFAIL [ 41%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_arraylike1d XFAIL [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_arraylike2d_drop XFAIL [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalNumerical::test_arraylike1d_drop XFAIL [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_array1d_col_error PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_recarray2d_error PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_array2d XPASS [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_array1d XPASS [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_array2d_drop XPASS [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_array1d_drop PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_recarray2d PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_recarray2dint PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_recarray1d PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_recarray1d_drop PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_recarray2d_drop PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_structarray2d PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_structarray2dint PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_structarray1d PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_structarray2d_drop PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_structarray1d_drop PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_arraylike2d XFAIL [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_arraylike1d XFAIL [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_arraylike2d_drop XFAIL [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestCategoricalString::test_arraylike1d_drop XFAIL [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::test_rec_issue302 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::test_issue302 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::test_pandas_const_series PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::test_pandas_const_series_prepend PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::test_pandas_const_df PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::test_pandas_const_df_prepend PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestNanDot::test_11 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestNanDot::test_12 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestNanDot::test_13 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestNanDot::test_14 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestNanDot::test_41 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestNanDot::test_23 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestNanDot::test_32 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestNanDot::test_24 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestNanDot::test_25 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestNanDot::test_66 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestEnsure2d::test_enfore_numpy PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestEnsure2d::test_pandas PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::TestEnsure2d::test_numpy PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::test_categorical_pandas_errors PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::test_categorical_series PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::test_categorical_dataframe PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_tools.py::test_categorical_errors PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_transform_model.py::test_standardize1 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_transform_model.py::test_standardize_ols PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_web.py::TestWeb::test_string PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_web.py::TestWeb::test_function PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_web.py::TestWeb::test_nothing PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/tests/test_web.py::TestWeb::test_errors PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_1d[True] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_1d[False] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_2d[True] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_2d[False] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_3d PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_right_squeeze_and_pad PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_contiguous PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_dtype PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_dot[True] XFAIL [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_dot[False] XFAIL [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_slice[True] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::TestArrayLike::test_slice[False] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_right_squeeze PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_wrap_pandas[True] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_wrap_pandas[False] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_wrap_pandas_append PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_optional_dict_like[dict] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_optional_dict_like[OrderedDict] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_optional_dict_like[CustomDict] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_optional_dict_like[None] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_optional_dict_like_error PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_string PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_optional_string PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_float_like[1.0] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_float_like[1.1] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_float_like[floating2] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_float_like[floating3] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_float_like[floating4] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_not_float_like[not_floating0] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_not_float_like[not_floating1] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_not_float_like[True] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_not_float_like[3.2] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_not_float_like[None] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_int_like[1.0] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_int_like[2] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_int_like[integer2] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_int_like[integer3] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[3.2] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[not_integer1] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[not_integer2] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[not_integer3] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[apple] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[not_integer5] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_not_int_like[not_integer6] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_bool_like[True] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_bool_like[False] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_bool_like[1] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_bool_like[1.2] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_bool_like[a] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_bool_like[] PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/validation/tests/test_validation.py::test_not_bool_like PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_burg.py::test_brockwell_davis_example_513 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_burg.py::test_brockwell_davis_example_514 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_burg.py::test_itsmr PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_burg.py::test_nonstationary_series PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_burg.py::test_invalid PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_burg.py::test_misc PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_brockwell_davis_example_511 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_itsmr PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_nonstationary_series PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_nonstationary_series_variance XFAIL [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_invalid PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_misc PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_brockwell_davis_example_661 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_brockwell_davis_example_662 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_integrated PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_integrated_invalid PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_results PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_iterations PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_misc PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_alternate_arma_estimators_valid PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_alternate_arma_estimators_invalid PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_arma_kwargs PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_brockwell_davis_example_517 PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_itsmr PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_initial_order XFAIL [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_invalid_orders XFAIL [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_nonconsecutive_lags PASSED [ 42%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_unbiased_error PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_brockwell_davis_example_515 PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_ma_itsmr PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_ma_invalid PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_brockwell_davis_example_524 PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_brockwell_davis_example_524_variance XFAIL [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_brockwell_davis_example_525 PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_brockwell_davis_example_541 PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_statespace PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_statespace_seasonal PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_statespace_nonconsecutive PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_integrated PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_misc PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_invalid PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_statespace.py::test_basic PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_statespace.py::test_start_params PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_yule_walker.py::test_brockwell_davis_example_511 PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_yule_walker.py::test_brockwell_davis_example_514 PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_yule_walker.py::test_itsmr PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_yule_walker.py::test_invalid PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_yule_walker.py::test_invalid_xfail XFAIL [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_default_trend PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_invalid PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_yule_walker PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_burg PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_hannan_rissanen PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_innovations PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_innovations_mle PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_statespace PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_low_memory PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_clone PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_append PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_init PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_set_params_single PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_set_params_single_nonconsecutive PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_set_params_multiple PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_set_poly_short_lags PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_set_poly_short_lags_nonconsecutive PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_set_poly_longer_lags PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_is_stationary PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_is_invertible PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_is_valid PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_repr_str PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-0-0-0-params0-p] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-0-0-0-params1-p] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-0-0-0-params2-p] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[2-0-0-0-params3-p] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[20-0-0-0-params4-p] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-1-0-0-params5-p] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-1-1-4-params6-p] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-1-0-0-params7-p] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-1-1-4-params8-p] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-0-0-0-params9-q] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-0-0-0-params10-q] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-0-0-0-params11-q] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[2-0-0-0-params12-q] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[20-0-0-0-params13-q] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-1-0-0-params14-q] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-1-1-4-params15-q] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-1-0-0-params16-q] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-1-1-4-params17-q] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-0-0-0-0-0-0-0-True-True-False] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-0-1-0-0-0-0-True-True-False] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-1-1-0-0-0-0-True-True-False] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-0-0-0-0-0-4-True-True-False] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-0-0-0-1-1-1-4-True-True-False] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-0-0-1-0-0-4-True-True-False] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-0-0-1-1-1-4-True-True-False] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-2-1-3-4-1-3-12-True-True-False] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-p8-0-0-1-0-0-4-True-True-False] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-0-0-0-0-0-Q9-4-True-True-False] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-p10-0-q10-P10-0-Q10-4-True-True-False] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-2-1-3-4-1-3-12-False-False-True] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-2-1-3-4-1-3-12-True-False-True] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[True-None-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-2-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[True-2-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[y-None-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-exog18-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[y-exog19-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[y-exog20-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[True-exog21-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[y-2-2-1-3-4-1-3-12-False-True-True] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_misc PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_invalid PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order0-seasonal_order0-None-None-None-valid0] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order1-seasonal_order1-None-None-None-valid1] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order2-seasonal_order2-None-None-None-valid2] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order3-seasonal_order3-None-None-None-valid3] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order4-seasonal_order4-None-None-None-valid4] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order5-seasonal_order5-True-None-None-valid5] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order6-seasonal_order6-False-None-None-valid6] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order7-seasonal_order7-None-True-None-valid7] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order8-seasonal_order8-None-False-None-valid8] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order9-seasonal_order9-None-None-True-valid9] PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_invalid_estimator PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_tools.py::test_standardize_lag_order_int PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_tools.py::test_standardize_lag_order_list_int PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_tools.py::test_standardize_lag_order_tuple_int PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_tools.py::test_standardize_lag_order_ndarray_int PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_tools.py::test_standardize_lag_order_list_bool PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_tools.py::test_standardize_lag_order_tuple_bool PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_tools.py::test_standardize_lag_order_ndarray_bool PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_tools.py::test_standardize_lag_order_misc PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_tools.py::test_standardize_lag_order_invalid PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/arima/tests/test_tools.py::test_validate_basic PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_base.py::test_pandas_nodates_index PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_base.py::test_predict_freq PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_base.py::test_keyerror_start_date PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_base.py::test_period_index PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_base.py::test_pandas_dates PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_base.py::test_get_predict_start_end PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_datetools.py::test_regex_matching_month PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_datetools.py::test_regex_matching_quarter PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_datetools.py::test_dates_from_range PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_instantiation_valid PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_prediction_increment_unsupported PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_prediction_increment_nonpandas PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_prediction_increment_pandas_noindex PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_prediction_increment_pandas_dates_daily PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_prediction_increment_pandas_dates_monthly PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_prediction_increment_pandas_dates_nanosecond PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_range_index PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_prediction_rangeindex PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_prediction_rangeindex_withstep PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_custom_index PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_nonmonotonic_periodindex PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_nonfull_periodindex XFAIL [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/base/tests/test_tsa_indexes.py::test_get_index_loc_quarterly PASSED [ 43%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::test_bking1d PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::test_bking2d PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::test_hpfilter PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::test_cfitz_filter PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::test_bking_pandas PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::test_cfitz_pandas PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::test_hpfilter_pandas PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_convolution PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_convolution2d PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_recursive PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_pandas PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_pandas2d PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_odd_length_filter PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::test_pandas_freq_decorator PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params0-ma_params0-1] XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params1-ma_params1-1] XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params2-ma_params2-1] XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params3-ma_params3-1] XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params4-ma_params4-1.123] XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params5-ma_params5-1.123] XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_brockwell_davis_ex533 PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_brockwell_davis_ex534 PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_filter_kalman_filter[ar_params0-ma_params0-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_filter_kalman_filter[ar_params1-ma_params1-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_filter_kalman_filter[ar_params2-ma_params2-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_filter_kalman_filter[ar_params3-ma_params3-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_filter_kalman_filter[ar_params4-ma_params4-1.123] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_filter_kalman_filter[ar_params5-ma_params5-1.123] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params0-ma_params0-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params1-ma_params1-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params2-ma_params2-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params3-ma_params3-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params4-ma_params4-1.123] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params5-ma_params5-1.123] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params0-1-ma_params0-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params1-1-ma_params1-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params2-1-ma_params2-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params3-1-ma_params3-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params4-1-ma_params4-1.123] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params5-1-ma_params5-1.123] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params6-2-ma_params6-1.123] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params0-ma_params0-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params1-ma_params1-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params2-ma_params2-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params3-ma_params3-1] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params4-ma_params4-1.123] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params5-ma_params5-1.123] PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/interp/tests/test_denton.py::test_denton_quarterly PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/interp/tests/test_denton.py::test_denton_quarterly2 PASSED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::test_predict XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::test_conditional_loglikelihoods XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR2Short::test_llf XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR2Short::test_fit XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR2Short::test_fit_em XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR2Short::test_filter_output XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR2Short::test_smoother_output XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR4::test_llf XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR4::test_fit XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR4::test_fit_em XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR4::test_filtered_regimes XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR4::test_smoothed_regimes XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR4::test_bse XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR2Switch::test_llf XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR2Switch::test_fit XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR2Switch::test_fit_em XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR2Switch::test_smoothed_marginal_probabilities XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR2Switch::test_predict XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR2Switch::test_bse XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1Switch::test_llf XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1Switch::test_fit XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1Switch::test_fit_em XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1Switch::test_filtered_regimes XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1Switch::test_smoothed_regimes XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1Switch::test_expected_durations XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1SwitchTVTP::test_llf XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1SwitchTVTP::test_fit XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1SwitchTVTP::test_fit_em SKIPPED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1SwitchTVTP::test_filtered_regimes XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1SwitchTVTP::test_smoothed_regimes XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1SwitchTVTP::test_expected_durations XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardo::test_llf XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardo::test_fit SKIPPED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardo::test_fit_em SKIPPED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardo::test_filtered_regimes XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardo::test_smoothed_regimes XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardo::test_expected_durations XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardoPandas::test_llf XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardoPandas::test_fit SKIPPED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardoPandas::test_fit_em SKIPPED [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardoPandas::test_filtered_regimes XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardoPandas::test_smoothed_regimes XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardoPandas::test_expected_durations XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConst::test_summary XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConst::test_llf XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConst::test_fit XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConst::test_fit_em XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConst::test_filter_output XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConst::test_smoothed_marginal_probabilities XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConst::test_predict XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConst::test_bse XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstShort::test_summary XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstShort::test_llf XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstShort::test_fit XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstShort::test_fit_em XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstShort::test_filter_output XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstShort::test_smoother_output XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstShort::test_hamilton_filter_order_zero XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstShort::test_hamilton_filter_order_zero_with_tvtp XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstShort::test_hamilton_filter_shape_checks XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1::test_summary XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1::test_llf XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1::test_fit XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1::test_fit_em XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1::test_bse XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog::test_summary XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog::test_llf XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog::test_fit_em XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog::test_fit XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog::test_predict XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog::test_bse XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog3::test_summary XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog3::test_llf XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog3::test_fit_em XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog3::test_fit XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestAreturnsConstL1Variance::test_summary XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestAreturnsConstL1Variance::test_llf XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestAreturnsConstL1Variance::test_fit_em XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestAreturnsConstL1Variance::test_fit XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestAreturnsConstL1Variance::test_bse XFAIL [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestMumpspcNoconstL1Variance::test_summary XPASS [ 44%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestMumpspcNoconstL1Variance::test_llf XPASS [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestMumpspcNoconstL1Variance::test_fit XFAIL [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::TestMumpspcNoconstL1Variance::test_fit_em XPASS [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::test_avoid_underflow XPASS [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_regression.py::test_exog_tvtp XPASS [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_switching.py::test_params PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_switching.py::test_init_endog PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_switching.py::test_init_exog_tvtp PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_switching.py::test_transition_matrix PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_switching.py::test_initial_probabilities PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_switching.py::test_logistic PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/tests/test_markov_switching.py::test_partials_logistic PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_using_collapsed PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_forecasts PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_forecasts_error PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_forecasts_error_cov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_filtered_state PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_filtered_state_cov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_predicted_state PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_predicted_state_cov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_loglike PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_smoothed_states PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_smoothed_states_cov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_smoothed_states_autocov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_smoothed_measurement_disturbance SKIPPED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_smoothed_measurement_disturbance_cov SKIPPED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_smoothed_state_disturbance PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_smoothed_state_disturbance_cov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_simulation_smoothed_state PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_simulation_smoothed_measurement_disturbance PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_simulation_smoothed_state_disturbance PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_using_collapsed PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_forecasts PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_forecasts_error PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_forecasts_error_cov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_filtered_state PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_filtered_state_cov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_predicted_state PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_predicted_state_cov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_loglike PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_smoothed_states PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_smoothed_states_cov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_smoothed_states_autocov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_smoothed_measurement_disturbance SKIPPED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_smoothed_measurement_disturbance_cov SKIPPED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_smoothed_state_disturbance PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_smoothed_state_disturbance_cov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_simulation_smoothed_state PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_simulation_smoothed_measurement_disturbance PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_simulation_smoothed_state_disturbance PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_using_alterate PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissing::test_using_collapsed PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissing::test_forecasts PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissing::test_forecasts_error PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissing::test_forecasts_error_cov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissing::test_filtered_state PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissing::test_filtered_state_cov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissing::test_predicted_state PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissing::test_predicted_state_cov PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissing::test_loglike PASSED [ 45%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissing::test_smoothed_states PASSED [ 45%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_plot_coefficients_of_determination XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_no_enforce XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_mle XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_loglike XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_aic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_bic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_dynamic_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_bse_approx XFAIL [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_params XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_results XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_plot_coefficients_of_determination XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_no_enforce XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_loglike XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_dynamic_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_mle XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_bse XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_aic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_bic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_summary XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_params XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_results XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_plot_coefficients_of_determination XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_no_enforce XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_mle XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_loglike XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_aic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_bic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_dynamic_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_bse_approx XFAIL [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_params XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_results XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_plot_coefficients_of_determination XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_no_enforce XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_mle XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_loglike XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_aic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_bic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_bse_approx XFAIL [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_dynamic_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_summary XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_params XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_results XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_plot_coefficients_of_determination XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_no_enforce XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_loglike XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_aic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_bic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_dynamic_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_bse_approx XFAIL [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_mle SKIPPED [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_summary XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_params XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_results XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_plot_coefficients_of_determination XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_no_enforce XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_loglike XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_aic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_bic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_dynamic_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_bse_approx XFAIL [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_mle XFAIL [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_params XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_results XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_plot_coefficients_of_determination XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_no_enforce XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_mle XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_loglike XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_aic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_bic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_bse_approx XFAIL [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_dynamic_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_params XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_results XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_plot_coefficients_of_determination XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_no_enforce XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_mle XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_loglike XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_aic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_dynamic_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_bse_approx XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_bic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_params XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_results XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_plot_coefficients_of_determination XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_no_enforce XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_mle XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_loglike XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_aic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_bic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_bse_approx XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_dynamic_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_params XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_results XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_plot_coefficients_of_determination XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_no_enforce XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_loglike XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_aic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_bic XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_bse_approx XFAIL [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_dynamic_predict XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_mle XPASS [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_misspecification PASSED [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_miscellaneous PASSED [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_predict_custom_index PASSED [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_forecast_exog PASSED [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_recreate_model PASSED [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_append_results PASSED [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_extend_results PASSED [ 48%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_apply_results PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py::test_start_params_nans PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLevelAnalytic::test_results PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLevelAnalyticDirect::test_results PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLinearTrendAnalytic::test_results PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLinearTrendAnalyticDirect::test_results PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLinearTrendAnalyticMissing::test_results PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::test_common_level_analytic PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::test_common_level_restricted_analytic PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_forecasts PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_forecasts_error PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_forecasts_error_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_filtered_state PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_filtered_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_predicted_state PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_predicted_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_kalman_gain PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_loglike PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state_autocov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_measurement_disturbance PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state_disturbance PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state_disturbance_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothing_error SKIPPED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_estimator PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_estimator_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_forecasts_error_diffuse_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_predicted_diffuse_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_simulation_smoothed_state XFAIL [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_initialization_approx PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_nobs_diffuse PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_initialization PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_forecasts PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_forecasts_error PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_forecasts_error_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_filtered_state PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_filtered_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_predicted_state PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_predicted_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_kalman_gain PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_loglike PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state_autocov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_measurement_disturbance PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state_disturbance PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state_disturbance_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothing_error SKIPPED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_estimator PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_forecasts_error_diffuse_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_predicted_diffuse_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_simulation_smoothed_state XFAIL [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_nobs_diffuse PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_initialization PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_forecasts PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_forecasts_error PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_forecasts_error_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_filtered_state PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_filtered_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_predicted_state PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_predicted_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_kalman_gain PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_loglike PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state_autocov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_measurement_disturbance PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state_disturbance PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state_disturbance_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothing_error SKIPPED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_estimator PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_estimator_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_forecasts_error_diffuse_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_predicted_diffuse_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_simulation_smoothed_state XFAIL [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_initialization_approx PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_nobs_diffuse PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_initialization PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_forecasts PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_forecasts_error PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_forecasts_error_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_filtered_state PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_filtered_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_predicted_state PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_predicted_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_kalman_gain PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_loglike PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state_autocov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_measurement_disturbance PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state_disturbance PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state_disturbance_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothing_error SKIPPED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_estimator PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_forecasts_error_diffuse_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_predicted_diffuse_state_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_simulation_smoothed_state XFAIL [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_nobs_diffuse PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_initialization PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_forecasts PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_forecasts_error PASSED [ 49%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_forecasts_error_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_filtered_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_filtered_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_predicted_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_predicted_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_kalman_gain PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_loglike PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state_autocov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_measurement_disturbance PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state_disturbance PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state_disturbance_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothing_error SKIPPED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_estimator PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_estimator_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_forecasts_error_diffuse_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_predicted_diffuse_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_simulation_smoothed_state XFAIL [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_initialization_approx PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_initialization PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_nobs_diffuse PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_forecasts PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_forecasts_error PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_filtered_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_filtered_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_predicted_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_predicted_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_kalman_gain PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_loglike PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state_autocov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_measurement_disturbance PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state_disturbance PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state_disturbance_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothing_error SKIPPED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_estimator PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_forecasts_error_diffuse_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_predicted_diffuse_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_simulation_smoothed_state XFAIL [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_initialization PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_nobs_diffuse PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_forecasts_error_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_forecasts PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_forecasts_error PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_forecasts_error_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_filtered_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_filtered_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_predicted_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_predicted_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_kalman_gain PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_loglike PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state_autocov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_measurement_disturbance PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state_disturbance PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state_disturbance_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothing_error SKIPPED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_scaled_smoothed_estimator PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_scaled_smoothed_estimator_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_forecasts_error_diffuse_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_predicted_diffuse_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_simulation_smoothed_state XFAIL [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_nobs_diffuse PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_initialization PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_initialization_approx PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_forecasts PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_forecasts_error PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_forecasts_error_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_filtered_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_predicted_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_kalman_gain PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_loglike PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state_autocov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_measurement_disturbance PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state_disturbance PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state_disturbance_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothing_error SKIPPED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_estimator PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_forecasts_error_diffuse_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_predicted_diffuse_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_simulation_smoothed_state XFAIL [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_nobs_diffuse PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_initialization PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_predicted_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_filtered_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_forecasts PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_forecasts_error PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_forecasts_error_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_filtered_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_filtered_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_predicted_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_predicted_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_kalman_gain PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_loglike PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state_autocov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_measurement_disturbance PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 50%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state_disturbance PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state_disturbance_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothing_error SKIPPED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_estimator PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_estimator_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_forecasts_error_diffuse_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_predicted_diffuse_state_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_simulation_smoothed_state XFAIL [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_initialization_approx PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_nobs_diffuse PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_initialization PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_forecasts PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_forecasts_error PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_forecasts_error_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_filtered_state_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_predicted_state_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_kalman_gain PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_loglike PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state_autocov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_measurement_disturbance PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state_disturbance PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state_disturbance_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothing_error SKIPPED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_estimator PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_forecasts_error_diffuse_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_predicted_diffuse_state_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_simulation_smoothed_state XFAIL [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_nobs_diffuse PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_initialization PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_predicted_state PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_filtered_state PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_forecasts PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_forecasts_error PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_forecasts_error_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_filtered_state PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_filtered_state_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_predicted_state PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_predicted_state_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_kalman_gain PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_loglike PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_state PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_state_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_state_autocov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_measurement_disturbance PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_state_disturbance PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_state_disturbance_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothing_error SKIPPED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_scaled_smoothed_estimator PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_scaled_smoothed_estimator_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_forecasts_error_diffuse_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_predicted_diffuse_state_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_simulation_smoothed_state XFAIL [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_initialization_approx PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_nobs_diffuse PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_initialization PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::test_irrelevant_state XFAIL [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::test_nondiagonal_obs_cov PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_fitted PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_output PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_forecasts PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_conf_int PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_initial_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_misc PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_fitted PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_output PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_forecasts PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_conf_int PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_initial_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_misc PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_fitted PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_output PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_forecasts PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_conf_int PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_initial_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_misc PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_fitted PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_output PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_forecasts PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_conf_int PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_initial_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_misc PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_mle_estimates PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_fitted PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_output PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_forecasts PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_initial_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_misc PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_conf_int PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_fitted PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_output PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_forecasts PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_conf_int PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_initial_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_misc PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_fitted PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_output PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_forecasts PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_conf_int PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_initial_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_states PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_misc PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_mle_estimates PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_fitted PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_output PASSED [ 51%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_forecasts PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_conf_int PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_initial_states PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_states PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_misc PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_fitted PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_output PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_forecasts PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_conf_int PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_initial_states PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_states PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_misc PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_fitted PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_output PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_forecasts PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_conf_int PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_initial_states PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_states PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_misc PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_mle_estimates PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendETSEstimated::test_fitted PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendETSEstimated::test_output PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendETSEstimated::test_forecasts PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendETSEstimated::test_initial_states PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendETSEstimated::test_states PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendETSEstimated::test_misc PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendETSEstimated::test_conf_int PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendETSEstimated::test_mle_estimates PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESKnownInitialization::test_given_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESKnownInitialization::test_estimated_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltKnownInitialization::test_given_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltKnownInitialization::test_estimated_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedKnownInitialization::test_given_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedKnownInitialization::test_estimated_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersKnownInitialization::test_given_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersKnownInitialization::test_estimated_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedKnownInitialization::test_given_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedKnownInitialization::test_estimated_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendKnownInitialization::test_given_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendKnownInitialization::test_estimated_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESHeuristicInitialization::test_heuristic PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltHeuristicInitialization::test_heuristic PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedHeuristicInitialization::test_heuristic PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersHeuristicInitialization::test_heuristic PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedHeuristicInitialization::test_heuristic PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendHeuristicInitialization::test_heuristic PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::test_concentrated_initialization PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESConcentratedInitialization::test_given_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESConcentratedInitialization::test_estimated_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltConcentratedInitialization::test_given_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltConcentratedInitialization::test_estimated_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedConcentratedInitialization::test_given_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedConcentratedInitialization::test_estimated_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersConcentratedInitialization::test_given_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersConcentratedInitialization::test_estimated_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedConcentratedInitialization::test_given_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedConcentratedInitialization::test_estimated_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendConcentratedInitialization::test_given_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendConcentratedInitialization::test_estimated_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestMultiIndex::test_fitted PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestMultiIndex::test_output PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestMultiIndex::test_forecasts PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestMultiIndex::test_initial_states PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestMultiIndex::test_states PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestMultiIndex::test_misc PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestMultiIndex::test_conf_int PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::test_invalid PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_fixed_params.py::test_fix_params PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_fixed_params.py::test_results_append PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_fixed_params.py::test_results_extend PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_fixed_params.py::test_results_apply PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_fixed_params.py::test_sarimax_invalid PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_fixed_params.py::test_structural_invalid PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_fixed_params.py::test_dynamic_factor_invalid PASSED [ 52%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_fixed_params.py::test_sarimax_nonconsecutive FAILED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_fixed_params.py::test_structural PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_fixed_params.py::test_dynamic_factor_diag_error_cov PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_fixed_params.py::test_score_shape PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_sarimax PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_structural PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_varmax PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_dynamic_factor PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_time_varying_ssm PASSED [ 52%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_time_varying_out_of_sample PASSED [ 52%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_time_varying_out_of_sample_anchored_end PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_pandas_univariate_rangeindex PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_pandas_univariate_dateindex PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_pandas_multivariate_rangeindex PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_pandas_multivariate_dateindex PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_impulse_responses.py::test_pandas_anchor PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_initialization.py::test_global_known PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_initialization.py::test_global_diffuse PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_initialization.py::test_global_approximate_diffuse PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_initialization.py::test_global_stationary PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_initialization.py::test_mixed_basic PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_initialization.py::test_mixed_stationary PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_initialization.py::test_nested PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_initialization.py::test_invalid PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Single::test_pickled_filter SKIPPED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Single::test_copied_filter SKIPPED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Single::test_loglike SKIPPED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Single::test_filtered_state SKIPPED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Double::test_loglike PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Double::test_filtered_state PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Double::test_pickled_filter PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Double::test_copied_filter PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987SingleComplex::test_pickled_filter SKIPPED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987SingleComplex::test_copied_filter SKIPPED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987SingleComplex::test_loglike SKIPPED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987SingleComplex::test_filtered_state SKIPPED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987DoubleComplex::test_loglike XFAIL [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987DoubleComplex::test_filtered_state XPASS [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987DoubleComplex::test_pickled_filter XPASS [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987DoubleComplex::test_copied_filter XPASS [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Conserve::test_loglike PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Conserve::test_filtered_state PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Conserve::test_pickled_filter PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987Conserve::test_copied_filter PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDouble::test_loglike PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDouble::test_pickled_filter PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDouble::test_copied_filter PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDouble::test_filtered_state PASSED [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDoubleComplex::test_loglike XFAIL [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDoubleComplex::test_pickled_filter XPASS [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDoubleComplex::test_copied_filter XPASS [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastDoubleComplex::test_filtered_state XPASS [ 52%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastConserve::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastConserve::test_pickled_filter PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastConserve::test_copied_filter PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ForecastConserve::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ConserveAll::test_pickled_filter PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ConserveAll::test_copied_filter PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ConserveAll::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1987ConserveAll::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989Conserve::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989Conserve::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ForecastDouble::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ForecastDouble::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ForecastDoubleComplex::test_loglike XFAIL [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ForecastDoubleComplex::test_filtered_state XPASS [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ForecastConserve::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ForecastConserve::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ConserveAll::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::TestClark1989ConserveAll::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_kalman.py::test_stationary_initialization PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_init_matrices_time_invariant PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_init_matrices_time_varying PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_wrapping PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_fit_misc PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_score_misc PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_from_formula PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_score_analytic_ar1 XFAIL [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_cov_params PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_transform XPASS [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_filter PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_params PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_results PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_predict PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_forecast PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_summary PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_basic_endog PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_numpy_endog PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_pandas_endog PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_diagnostics PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_diagnostics_nile_eviews PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_diagnostics_nile_durbinkoopman PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_prediction_results PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_lutkepohl_information_criteria PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_append_extend_apply_invalid PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_mlemodel.py::test_integer_params PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_scaled_smoothed_estimator PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_scaled_smoothed_estimator_cov PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_forecasts PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_forecasts_error PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_forecasts_error_cov PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_predicted_states PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_predicted_states_cov PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_states PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_states_cov PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_forecasts PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_state_disturbance PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_state_disturbance_cov PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_measurement_disturbance PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestIntercepts::test_smoothed_measurement_disturbance_cov PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::test_large_kposdef PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_dimensions SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_loglike SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_scaled_smoothed_estimator SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_scaled_smoothed_estimator_cov SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_forecasts SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_forecasts_error SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_forecasts_error_cov SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_predicted_states SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_predicted_states_cov SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_smoothed_states SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_smoothed_states_cov SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_smoothed_state_disturbance SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_smoothed_state_disturbance_cov SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_smoothed_measurement_disturbance SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_models.py::TestLargeStateCovAR1::test_smoothed_measurement_disturbance_cov SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_options.py::TestOptions::test_filter_methods PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_options.py::TestOptions::test_inversion_methods PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_options.py::TestOptions::test_stability_methods PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_options.py::TestOptions::test_conserve_memory PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_options.py::TestOptions::test_smoother_outputs PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_options.py::TestOptions::test_simulation_outputs PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_pickle.py::test_pickle_fit_sarimax XPASS [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_pickle.py::test_unobserved_components_pickle XPASS [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_pickle.py::test_kalman_filter_pickle XPASS [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_pickle.py::test_representation_pickle XPASS [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_prediction.py::test_predict_dates PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_prediction.py::test_memory_no_predicted PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987Single::test_loglike SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987Single::test_filtered_state SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987Double::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987Double::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987SingleComplex::test_loglike SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987SingleComplex::test_filtered_state SKIPPED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987DoubleComplex::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987DoubleComplex::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987Conserve::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987Conserve::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ForecastDouble::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ForecastDouble::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ForecastDoubleComplex::test_loglike XFAIL [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ForecastDoubleComplex::test_filtered_state XPASS [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ForecastConserve::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ForecastConserve::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ConserveAll::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1987ConserveAll::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989::test_kalman_gain PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989Conserve::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989Conserve::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ForecastDouble::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ForecastDouble::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ForecastDoubleComplex::test_loglike XFAIL [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ForecastDoubleComplex::test_filtered_state XPASS [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ForecastConserve::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ForecastConserve::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ConserveAll::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989ConserveAll::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989PartialMissing::test_loglike PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989PartialMissing::test_filtered_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::TestClark1989PartialMissing::test_predicted_state PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_slice_notation PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_representation PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_bind PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_initialization PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_init_matrices_time_invariant PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_init_matrices_time_varying PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_no_endog PASSED [ 53%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_cython PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_filter PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_loglike PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_predict PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_standardized_forecasts_error PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_simulate PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_impulse_responses PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_representation.py::test_missing PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_loglike XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_aic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_bic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_hqic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_mle XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_bse XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_t_test XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestRealGDPARStata::test_filtered_state PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestRealGDPARStata::test_standardized_forecasts_error PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMAStationary::test_loglike XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMAStationary::test_aic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMAStationary::test_bic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMAStationary::test_hqic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMAStationary::test_standardized_forecasts_error XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMAStationary::test_mle XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMAStationary::test_bse XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMAStationary::test_bse_approx XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMAStationary::test_bse_oim XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMAStationary::test_bse_robust XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMADiffuse::test_loglike XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMADiffuse::test_aic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMADiffuse::test_bic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMADiffuse::test_hqic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMADiffuse::test_standardized_forecasts_error XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMADiffuse::test_mle XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMADiffuse::test_bse XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMADiffuse::test_bse_approx XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestARIMADiffuse::test_bse_oim XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAdditiveSeasonal::test_loglike XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAdditiveSeasonal::test_aic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAdditiveSeasonal::test_bic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAdditiveSeasonal::test_hqic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAdditiveSeasonal::test_standardized_forecasts_error XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAdditiveSeasonal::test_mle XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAdditiveSeasonal::test_bse XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAdditiveSeasonal::test_bse_approx XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAdditiveSeasonal::test_bse_oim XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHamilton::test_loglike XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHamilton::test_aic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHamilton::test_bic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHamilton::test_hqic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHamilton::test_standardized_forecasts_error XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHamilton::test_mle XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHamilton::test_bse XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHamilton::test_bse_approx XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHamilton::test_bse_oim XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHarvey::test_loglike XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHarvey::test_aic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHarvey::test_bic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHarvey::test_hqic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHarvey::test_standardized_forecasts_error XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHarvey::test_mle XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHarvey::test_bse XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHarvey::test_bse_approx XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineHarvey::test_bse_oim XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineStateDifferencing::test_loglike XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineStateDifferencing::test_aic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineStateDifferencing::test_hqic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineStateDifferencing::test_standardized_forecasts_error XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineStateDifferencing::test_bic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineStateDifferencing::test_mle XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineStateDifferencing::test_bse XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineStateDifferencing::test_bse_approx XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestAirlineStateDifferencing::test_bse_oim XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanMLERegression::test_loglike XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanMLERegression::test_aic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanMLERegression::test_bic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanMLERegression::test_hqic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanMLERegression::test_standardized_forecasts_error XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanMLERegression::test_mle XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanMLERegression::test_bse XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanMLERegression::test_bse_approx XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanMLERegression::test_bse_oim XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanStateRegression::test_hqic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanStateRegression::test_standardized_forecasts_error XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanStateRegression::test_mle XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanStateRegression::test_regression_parameters XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanStateRegression::test_loglike XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanStateRegression::test_aic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanStateRegression::test_bic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanStateRegression::test_bse XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanStateRegression::test_bse_approx XFAIL [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanStateRegression::test_bse_oim XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanPredict::test_hqic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanPredict::test_standardized_forecasts_error XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanPredict::test_loglike XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanPredict::test_aic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanPredict::test_bic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanPredict::test_predict XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanPredict::test_dynamic_predict XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanForecast::test_hqic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanForecast::test_standardized_forecasts_error XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanForecast::test_loglike XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanForecast::test_aic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanForecast::test_bic XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanForecast::test_forecast XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::TestFriedmanForecast::test_dynamic_forecast XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar::test_loglike PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar::test_start_params PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar::test_transform_untransform PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar::test_results XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar::test_plot_diagnostics PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar::test_predict PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar::test_init_keys_replicate PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_as_polynomial::test_loglike PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_as_polynomial::test_start_params PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_as_polynomial::test_transform_untransform PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_as_polynomial::test_results XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_as_polynomial::test_plot_diagnostics PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_as_polynomial::test_predict PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_as_polynomial::test_init_keys_replicate PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_loglike PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_start_params PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_transform_untransform PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_results XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_plot_diagnostics PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_predict PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_init_keys_replicate PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_loglike PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_start_params PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_transform_untransform PASSED [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_results XPASS [ 54%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_plot_diagnostics PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_predict PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_init_keys_replicate PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_polynomial::test_loglike PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_polynomial::test_start_params PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_polynomial::test_transform_untransform PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_polynomial::test_results XPASS [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_polynomial::test_plot_diagnostics PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_polynomial::test_predict PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_trend_polynomial::test_init_keys_replicate PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diff::test_loglike PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diff::test_start_params PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diff::test_transform_untransform PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diff::test_results XPASS [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diff::test_plot_diagnostics PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diff::test_predict PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diff::test_init_keys_replicate PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_seasonal_diff::test_loglike PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_seasonal_diff::test_start_params PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_seasonal_diff::test_transform_untransform PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_seasonal_diff::test_results XPASS [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_seasonal_diff::test_plot_diagnostics PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_seasonal_diff::test_predict PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_seasonal_diff::test_init_keys_replicate PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diffuse::test_loglike PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diffuse::test_start_params PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diffuse::test_transform_untransform PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diffuse::test_results XPASS [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diffuse::test_plot_diagnostics PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diffuse::test_predict PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_diffuse::test_init_keys_replicate PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_no_enforce::test_loglike PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_no_enforce::test_start_params PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_no_enforce::test_transform_untransform PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_no_enforce::test_results XPASS [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_no_enforce::test_plot_diagnostics PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_no_enforce::test_predict PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_no_enforce::test_init_keys_replicate PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous::test_loglike PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous::test_start_params PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous::test_transform_untransform PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous::test_results XPASS [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous::test_plot_diagnostics PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous::test_predict PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous::test_init_keys_replicate PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous_in_state::test_start_params PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous_in_state::test_transform_untransform PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous_in_state::test_results XPASS [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous_in_state::test_plot_diagnostics PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous_in_state::test_predict PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous_in_state::test_init_keys_replicate PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous_in_state::test_loglike PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous_in_state::test_regression_coefficient PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_loglike PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_start_params PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_transform_untransform PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_results XPASS [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_plot_diagnostics PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_predict PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma::test_init_keys_replicate PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma_as_polynomial::test_loglike PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma_as_polynomial::test_start_params PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma_as_polynomial::test_transform_untransform PASSED [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma_as_polynomial::test_results XPASS [ 55%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py::Test_ma_as_polynomial::test_plot_diagnostics PASSED [ 55%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_forecasts PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_forecasts_error PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_forecasts_error_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_filtered_state PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_filtered_state_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_predicted_state PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_predicted_state_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_loglike PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_smoothed_states PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_smoothed_states_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_smoothed_measurement_disturbance SKIPPED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_smoothed_measurement_disturbance_cov SKIPPED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_smoothed_state_disturbance PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_smoothed_state_disturbance_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_simulation_smoothed_state PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_simulation_smoothed_measurement_disturbance SKIPPED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_simulation_smoothed_state_disturbance PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_using_univariate PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_forecasts_error_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_filtered_state PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_filtered_state_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_predicted_state PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_predicted_state_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_loglike PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_smoothed_states PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_smoothed_states_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_smoothed_measurement_disturbance SKIPPED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_smoothed_measurement_disturbance_cov SKIPPED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_smoothed_state_disturbance PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_smoothed_state_disturbance_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_simulation_smoothed_state PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_simulation_smoothed_measurement_disturbance SKIPPED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_simulation_smoothed_state_disturbance PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_forecasts PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_forecasts_error PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_using_univariate PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_forecasts_error_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_filtered_state PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_filtered_state_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_predicted_state PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_predicted_state_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_loglike PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_smoothed_states PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_smoothed_states_cov PASSED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_smoothed_measurement_disturbance SKIPPED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_smoothed_measurement_disturbance_cov SKIPPED [ 61%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_smoothed_state_disturbance PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_smoothed_state_disturbance_cov PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_simulation_smoothed_state PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_simulation_smoothed_measurement_disturbance SKIPPED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_simulation_smoothed_state_disturbance PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_forecasts PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_forecasts_error PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_forecasts PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_forecasts_error PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_forecasts_error_cov PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_filtered_state PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_filtered_state_cov PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_predicted_state PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_predicted_state_cov PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_loglike PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_smoothed_states PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_smoothed_states_cov PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_smoothed_measurement_disturbance SKIPPED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_smoothed_measurement_disturbance_cov SKIPPED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_smoothed_state_disturbance PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_smoothed_state_disturbance_cov PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_simulation_smoothed_state PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_simulation_smoothed_measurement_disturbance SKIPPED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_simulation_smoothed_state_disturbance PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_univariate.py::test_time_varying_transition PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_var.py::test_var_basic PASSED [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_var.py::test_var_c XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_var.py::test_var_ct XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_var.py::test_var_ct_as_exog0 XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_var.py::test_var_ct_as_exog1 XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_var.py::test_var_ctt XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_var.py::test_var_ct_exog XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_var.py::test_var_c_2exog XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_mle XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_params XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_results XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_loglike XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_aic XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_bic XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_standardized_forecasts_error XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_predict XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_dynamic_predict XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_bse_approx XFAIL [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_bse_oim XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR::test_summary XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_mle XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_params XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_results XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_loglike XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_aic XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_bic XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_standardized_forecasts_error XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_predict XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_dynamic_predict XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_bse_approx XFAIL [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_bse_oim XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_summary XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_params XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_results XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_loglike XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_standardized_forecasts_error XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_predict XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_dynamic_predict XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_mle XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_bse_approx XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_bse_oim XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_aic XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_bic XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_representation XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_summary XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_mle XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_params XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_results XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_loglike XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_standardized_forecasts_error XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_predict XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_dynamic_predict XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_bse_approx XFAIL [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_bse_oim XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_aic XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_bic XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_params XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_results XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_loglike XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_standardized_forecasts_error XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_mle XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_aic XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_bic XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_bse_approx XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_bse_oim XPASS [ 62%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_predict XPASS [ 62%]
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../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 63%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 64%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 65%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 66%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 67%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 68%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 69%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 70%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 71%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 72%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 73%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 74%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 75%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 76%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSConstant::test_params PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSConstant::test_bse PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSConstant::test_llf PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSConstant::test_fpe PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSConstant::test_pickle PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSConstant::test_summary PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSConstant::test_pvalues PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSConstant::test_predict PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSNoConstant::test_params PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSNoConstant::test_bse PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSNoConstant::test_llf PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSNoConstant::test_fpe PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSNoConstant::test_pickle PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSNoConstant::test_summary PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSNoConstant::test_pvalues PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSNoConstant::test_predict PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAROLSNoConstant::test_mle PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestARMLEConstant::test_predict PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestARMLEConstant::test_dynamic_predict PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutolagAR::test_ic PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_ar_dates PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_ar_named_series PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_ar_start_params PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_ar_series PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_ar_select_order PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_ar_select_order_tstat PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_constant_column_trend PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_summary_corner PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_at_repeated_fit PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_ar_errors PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_ar_score PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_bestlag_stop PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_roots PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_resids_mle PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_ar_repeated_fit PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_ar_predict_no_fit PASSED [ 77%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back: None] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back: 12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back: None] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back: 12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back: None] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back: 12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back: None] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back: 12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back: None] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back: 12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back: None] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back: 12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back: None] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back: 12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 78%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 79%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 80%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 81%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 82%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 83%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 87%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%]
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%]
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=================================== FAILURES ===================================
_________________________ test_sarimax_nonconsecutive __________________________
def test_sarimax_nonconsecutive():
# SARIMAX allows using non-consecutive lag orders, which implicitly fix
# AR coefficients to zeros, so we can test explicitly fixed AR coefficients
# against this
endog = macrodata['infl']
# y_t = \phi_1 y_{t-1} + \phi_4 y_{t-4} + \varepsilon_t
# Note: because the transformation will not respect the parameter
# constraints, we will need to set enforce_stationarity=False; set it to
# False here too so that they both are the same model
mod1 = sarimax.SARIMAX(endog, order=([1, 0, 0, 1], 0, 0),
enforce_stationarity=False)
mod2 = sarimax.SARIMAX(endog, order=(4, 0, 0), enforce_stationarity=False)
# Start pretty close to optimum to speed up test
start_params = [0.6, 0.2, 6.4]
res1 = mod1.fit(start_params, disp=False)
res2 = mod2.fit_constrained({'ar.L2': 0, 'ar.L3': 0}, res1.params,
includes_fixed=False, disp=False)
# Check that the right parameters were fixed
assert_equal(res1.fixed_params, [])
assert_equal(res2.fixed_params, ['ar.L2', 'ar.L3'])
# Check that MLE finds the same parameters in either case
desired = np.r_[res1.params[0], 0, 0, res1.params[1:]]
assert_allclose(res2.params, desired)
# Now smooth at the actual parameters (to allow high precision testing
# below, even if there are small differences between MLE fitted parameters)
with mod2.fix_params({'ar.L2': 0, 'ar.L3': 0}):
res2 = mod2.smooth(res1.params)
> check_results(res1, res2, check_lutkepohl=True)
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_fixed_params.py:504:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
res1 = <statsmodels.tsa.statespace.sarimax.SARIMAXResultsWrapper object at 0xa56b16e8>
res2 = <statsmodels.tsa.statespace.sarimax.SARIMAXResultsWrapper object at 0xa57d2928>
check_lutkepohl = True, check_params = True
def check_results(res1, res2, check_lutkepohl=False, check_params=True):
# Check other results
assert_allclose(res2.nobs, res1.nobs)
assert_allclose(res2.nobs_diffuse, res1.nobs_diffuse)
assert_allclose(res2.nobs_effective, res1.nobs_effective)
assert_allclose(res2.k_diffuse_states, res1.k_diffuse_states)
assert_allclose(res2.df_model, res1.df_model)
assert_allclose(res2.df_resid, res1.df_resid)
assert_allclose(res2.llf, res1.llf)
assert_allclose(res2.aic, res1.aic)
assert_allclose(res2.bic, res1.bic)
assert_allclose(res2.hqic, res1.hqic)
if check_lutkepohl:
assert_allclose(res2.info_criteria('aic', 'lutkepohl'),
res1.info_criteria('aic', 'lutkepohl'))
assert_allclose(res2.info_criteria('bic', 'lutkepohl'),
res1.info_criteria('bic', 'lutkepohl'))
assert_allclose(res2.info_criteria('hqic', 'lutkepohl'),
res1.info_criteria('hqic', 'lutkepohl'))
assert_allclose(res2.llf_obs, res1.llf_obs)
assert_allclose(res2.fittedvalues, res1.fittedvalues)
assert_allclose(res2.fittedvalues, res1.fittedvalues)
if check_params:
# Check parameter-related values
mask_free = res2._free_params_index
mask_fixed = res2._fixed_params_index
assert_allclose(res2.pvalues[mask_free], res1.pvalues)
assert_allclose(res2.pvalues[mask_fixed], np.nan)
assert_allclose(res2.bse[mask_free], res1.bse)
assert_allclose(res2.bse[mask_fixed], np.nan)
assert_allclose(res2.zvalues[mask_free], res1.zvalues)
assert_allclose(res2.zvalues[mask_fixed], np.nan)
# Check parameter covariance matrix
mask_free = np.ix_(res2._free_params_index, res2._free_params_index)
mask_fixed = np.ix_(res2._fixed_params_index, res2._fixed_params_index)
assert_allclose(res2.cov_params_default.values[mask_free],
res1.cov_params_default)
assert_allclose(res2.cov_params_default.values[mask_fixed], np.nan)
> assert_allclose(res2.cov_params_approx.values[mask_free],
res1.cov_params_approx)
E AssertionError:
E Not equal to tolerance rtol=1e-07, atol=0
E
E Mismatch: 100%
E Max absolute difference: 0.00000015
E Max relative difference: 0.00007651
E x: array([[ 0.002962, -0.001403, -0. ],
E [-0.001403, 0.000665, 0. ],
E [-0. , 0. , -0. ]])
E y: array([[ 0.002961, -0.001403, -0. ],
E [-0.001403, 0.000665, 0. ],
E [-0. , 0. , -0. ]])
../.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_fixed_params.py:435: AssertionError
=============================== warnings summary ===============================
/usr/lib/python3/dist-packages/pandas/io/stata.py:918
tsa/statespace/tests/test_varmax.py::TestVARMA::test_params
tsa/statespace/tests/test_varmax.py::TestVMA1::test_params
/usr/lib/python3/dist-packages/pandas/io/stata.py:918: UserWarning: Non-x86 system detected, Stata format I/O may give wrong results - https://bugs.debian.org/877419
warnings.warn(warn_stata_platform)
base/tests/test_generic_methods.py::TestGenericOLS::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericOLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericOLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericWLS::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericWLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericWLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericLogit::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericLogit::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericLogit::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericRLM::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericRLM::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLM::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericGLM::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLM::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_collinear
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/model.py:1362: RuntimeWarning: invalid value encountered in true_divide
return self.params / self.bse
base/tests/test_generic_methods.py::TestGenericOLS::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericOLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericOLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericWLS::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericWLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericWLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericLogit::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericLogit::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericLogit::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericRLM::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericRLM::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLM::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericGLM::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLM::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_collinear
base/tests/test_screening.py::test_poisson_screening
base/tests/test_screening.py::test_logit_screening
discrete/tests/test_conditional.py::test_conditional_mnlogit_3d
regression/tests/test_lme.py::TestMixedLM::test_regularized
regression/tests/test_regression.py::test_fvalue_implicit_constant
sandbox/regression/tests/test_gmm.py::test_noconstant
stats/tests/test_anova.py::TestAnovaLMCompare::test_results
stats/tests/test_anova.py::TestAnovaLMCompareNoconstant::test_results
stats/tests/test_contingency_tables.py::TestStratified1::test_pandas
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::test_power_solver_warn
stats/tests/test_tost.py::test_tost_asym
tsa/statespace/tests/test_varmax.py::test_misc_exog
tsa/tests/test_stattools.py::TestACFMissing::test_raise
/usr/lib/python3/dist-packages/scipy/stats/_distn_infrastructure.py:901: RuntimeWarning: invalid value encountered in greater
return (a < x) & (x < b)
base/tests/test_generic_methods.py::TestGenericOLS::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericOLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericOLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericWLS::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericWLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericWLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericLogit::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericLogit::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericLogit::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericRLM::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericRLM::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLM::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericGLM::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLM::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_collinear
base/tests/test_screening.py::test_poisson_screening
base/tests/test_screening.py::test_logit_screening
discrete/tests/test_conditional.py::test_conditional_mnlogit_3d
regression/tests/test_lme.py::TestMixedLM::test_regularized
regression/tests/test_regression.py::test_fvalue_implicit_constant
sandbox/regression/tests/test_gmm.py::test_noconstant
stats/tests/test_anova.py::TestAnovaLMCompare::test_results
stats/tests/test_anova.py::TestAnovaLMCompareNoconstant::test_results
stats/tests/test_contingency_tables.py::TestStratified1::test_pandas
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::test_power_solver_warn
stats/tests/test_tost.py::test_tost_asym
tsa/statespace/tests/test_varmax.py::test_misc_exog
tsa/tests/test_stattools.py::TestACFMissing::test_raise
/usr/lib/python3/dist-packages/scipy/stats/_distn_infrastructure.py:901: RuntimeWarning: invalid value encountered in less
return (a < x) & (x < b)
base/tests/test_generic_methods.py::TestGenericOLS::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericOLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericOLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericOLSOneExog::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericWLS::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericWLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericWLS::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoisson::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericPoissonOffset::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericNegativeBinomial::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericLogit::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericLogit::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericLogit::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericRLM::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericRLM::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLM::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericGLM::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLM::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_constrained
base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_collinear
base/tests/test_generic_methods.py::TestGenericGLMPoissonOffset::test_zero_collinear
base/tests/test_screening.py::test_poisson_screening
base/tests/test_screening.py::test_logit_screening
discrete/tests/test_conditional.py::test_conditional_mnlogit_3d
regression/tests/test_regression.py::test_fvalue_implicit_constant
sandbox/regression/tests/test_gmm.py::test_noconstant
stats/tests/test_anova.py::TestAnovaLMCompare::test_results
stats/tests/test_anova.py::TestAnovaLMCompareNoconstant::test_results
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::TestFtestAnovaPower::test_power_plot
stats/tests/test_power.py::test_power_solver_warn
stats/tests/test_tost.py::test_tost_asym
tsa/statespace/tests/test_varmax.py::test_misc_exog
tsa/tests/test_stattools.py::TestACFMissing::test_raise
/usr/lib/python3/dist-packages/scipy/stats/_distn_infrastructure.py:1892: RuntimeWarning: invalid value encountered in less_equal
cond2 = cond0 & (x <= _a)
base/tests/test_penalized.py::TestPenalizedPoissonOraclePenalized2::test_params_table
base/tests/test_penalized.py::TestPenalizedPoissonOraclePenalized2HC::test_params_table
base/tests/test_penalized.py::TestPenalizedGLMBinomCountOracleHC::test_params_table
base/tests/test_penalized.py::TestPenalizedGLMBinomCountOracleHC2::test_params_table
base/tests/test_shrink_pickle.py::TestRemoveDataPickleNegativeBinomial::test_remove_data_pickle
base/tests/test_shrink_pickle.py::TestRemoveDataPickleNegativeBinomial::test_remove_data_docstring
base/tests/test_shrink_pickle.py::TestRemoveDataPickleNegativeBinomial::test_pickle_wrapper
discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_params
discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_params
discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_params
discrete/tests/test_count_model.py::TestZeroInflatedPoisson_predict::test_mean
discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_minimize
discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_minimize
discrete/tests/test_discrete.py::TestCVXOPT::test_cvxopt_versus_slsqp
discrete/tests/test_discrete.py::TestLogitL1Compatability::test_params
discrete/tests/test_discrete.py::TestL1AlphaZeroLogit::test_basic_results
discrete/tests/test_discrete.py::TestL1AlphaZeroLogit::test_converged
discrete/tests/test_discrete.py::TestNegativeBinomialNB1Null::test_llnull
discrete/tests/test_discrete.py::TestNegativeBinomialNBP1Null::test_llnull
genmod/tests/test_glm.py::TestGlmGaussianGradient::test_params
tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_integrated
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/model.py:567: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warn("Maximum Likelihood optimization failed to converge. "
discrete/tests/test_constrained.py::TestGLMLogitConstrained1::test_basic_method
tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_misc
tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_misc
tsa/statespace/tests/test_exponential_smoothing.py::TestMultiIndex::test_misc
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/model.py:1362: RuntimeWarning: divide by zero encountered in true_divide
return self.params / self.bse
discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_fit_regularized
discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_fit_regularized
discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_fit_regularized
discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_fit_regularized
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 4 out of 4 parameters
Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_fit_regularized
discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_fit_regularized
discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_fit_regularized
discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_fit_regularized
discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_fit_regularized
discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_fit_regularized
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/l1_solvers_common.py:144: ConvergenceWarning: Could not trim params automatically due to failed QC check. Trimming using trim_mode == 'size' will still work.
warnings.warn(msg, ConvergenceWarning)
discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_fit_regularized
discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_fit_regularized
discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_fit_regularized
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 3 out of 6 parameters
Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_fit_regularized
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 1 out of 5 parameters
Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_fit_regularized
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 3 out of 7 parameters
Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_null
discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict2::test_mean
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/model.py:547: HessianInversionWarning: Inverting hessian failed, no bse or cov_params available
warn('Inverting hessian failed, no bse or cov_params '
discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_fit_regularized
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 1 out of 2 parameters
Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_fit_regularized
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 1 out of 3 parameters
Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_fit_regularized
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 2 out of 5 parameters
Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_params
discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_params
discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_fit_regularized
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/discrete/discrete_model.py:1016: RuntimeWarning: overflow encountered in exp
return np.sum(-np.exp(XB) + endog*XB - gammaln(endog+1))
discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_fit_regularized
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 8 out of 10 parameters
Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_fit_regularized
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 2 out of 11 parameters
Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers
warnings.warn(message, ConvergenceWarning)
graphics/tests/test_tsaplots.py::test_plot_pacf
graphics/tests/test_tsaplots.py::test_plot_pacf
graphics/tests/test_tsaplots.py::test_plot_pacf_kwargs
graphics/tests/test_tsaplots.py::test_plot_pacf_kwargs
graphics/tests/test_tsaplots.py::test_plot_pacf_kwargs
graphics/tests/test_tsaplots.py::test_plot_pacf_irregular
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/linear_model.py:1406: RuntimeWarning: invalid value encountered in sqrt
return rho, np.sqrt(sigmasq)
nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_unordered_CV_LS
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/kernel_density.py:679: RuntimeWarning: invalid value encountered in double_scalars
CV += (G / m_x ** 2) - 2 * (f_X_Y / m_x)
nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuousdata_lc_cvls
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/kernel_regression.py:251: RuntimeWarning: invalid value encountered in true_divide
B_x = (G_numer * d_fx - G_denom * d_mx) / (G_denom**2)
nonparametric/tests/test_kernels.py::TestBiweight::test_smoothconf
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py:81: RuntimeWarning: invalid value encountered in greater
mask = np.abs(se - res_se) > (0.2 + 0.2 * res_se)
regression/tests/test_dimred.py::test_covreduce
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/dimred.py:691: UserWarning: CovReduce optimization did not converge, |g|=1.287955
warnings.warn(msg)
regression/tests/test_glsar_gretl.py::TestGLSARGretl::test_all
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_glsar_gretl.py:126: FutureWarning: the 'maxlag' keyword is deprecated, use 'nlags' instead
sm_arch = smsdia.het_arch(res.wresid, maxlag=4)
regression/tests/test_glsar_gretl.py::TestGLSARGretl::test_all
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_glsar_gretl.py:159: FutureWarning: the 'maxlag' keyword is deprecated, use 'nlags' instead
sm_arch = smsdia.het_arch(res.wresid, maxlag=4)
regression/tests/test_glsar_gretl.py::TestGLSARGretl::test_all
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/tests/test_glsar_gretl.py:395: FutureWarning: the 'maxlag' keyword is deprecated, use 'nlags' instead
sm_arch = smsdia.het_arch(res.resid, maxlag=4)
regression/tests/test_lme.py::TestMixedLM::test_regularized
stats/tests/test_contingency_tables.py::TestStratified1::test_pandas
/usr/lib/python3/dist-packages/scipy/stats/_distn_infrastructure.py:1807: RuntimeWarning: invalid value encountered in greater_equal
cond2 = (x >= _b) & cond0
regression/tests/test_processreg.py::test_formulas
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/regression/process_regression.py:632: UserWarning: Fitting did not converge, |gradient|=0.000032
warnings.warn(msg)
regression/tests/test_recursive_ls.py::test_endog
regression/tests/test_recursive_ls.py::test_ols
regression/tests/test_recursive_ls.py::test_glm
regression/tests/test_recursive_ls.py::test_glm_constrained
regression/tests/test_recursive_ls.py::test_filter
regression/tests/test_recursive_ls.py::test_estimates
regression/tests/test_recursive_ls.py::test_plots
regression/tests/test_recursive_ls.py::test_plots
regression/tests/test_recursive_ls.py::test_resid_recursive
regression/tests/test_recursive_ls.py::test_cusum
regression/tests/test_recursive_ls.py::test_stata
regression/tests/test_recursive_ls.py::test_constraints_stata
regression/tests/test_recursive_ls.py::test_multiple_constraints
regression/tests/test_recursive_ls.py::test_fix_params
tsa/arima/estimators/tests/test_gls.py::test_alternate_arma_estimators_valid
tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_statespace
tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_statespace_seasonal
tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_statespace_nonconsecutive
tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_integrated
tsa/arima/estimators/tests/test_statespace.py::test_basic
tsa/arima/estimators/tests/test_statespace.py::test_start_params
tsa/arima/tests/test_model.py::test_default_trend
tsa/arima/tests/test_model.py::test_invalid
tsa/arima/tests/test_model.py::test_yule_walker
tsa/arima/tests/test_model.py::test_burg
tsa/arima/tests/test_model.py::test_hannan_rissanen
tsa/arima/tests/test_model.py::test_innovations
tsa/arima/tests/test_model.py::test_innovations_mle
tsa/arima/tests/test_model.py::test_statespace
tsa/arima/tests/test_model.py::test_low_memory
tsa/arima/tests/test_model.py::test_clone
tsa/arima/tests/test_model.py::test_append
tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params0-ma_params0-1]
tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params1-ma_params1-1]
tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params2-ma_params2-1]
tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params3-ma_params3-1]
tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params4-ma_params4-1.123]
tsa/innovations/tests/test_arma_innovations.py::test_innovations_algo_filter_kalman_filter[ar_params5-ma_params5-1.123]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_filter_kalman_filter[ar_params0-ma_params0-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_filter_kalman_filter[ar_params1-ma_params1-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_filter_kalman_filter[ar_params2-ma_params2-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_filter_kalman_filter[ar_params3-ma_params3-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_filter_kalman_filter[ar_params4-ma_params4-1.123]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_filter_kalman_filter[ar_params5-ma_params5-1.123]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params0-ma_params0-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params1-ma_params1-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params2-ma_params2-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params3-ma_params3-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params4-ma_params4-1.123]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_innovations_algo_direct_filter_kalman_filter[ar_params5-ma_params5-1.123]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params0-1-ma_params0-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params1-1-ma_params1-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params2-1-ma_params2-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params3-1-ma_params3-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params4-1-ma_params4-1.123]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params5-1-ma_params5-1.123]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_integrated_process[ar_params6-2-ma_params6-1.123]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params0-ma_params0-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params1-ma_params1-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params2-ma_params2-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params3-ma_params3-1]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params4-ma_params4-1.123]
tsa/innovations/tests/test_cython_arma_innovations_fast.py::test_regression_with_arma_errors[ar_params5-ma_params5-1.123]
tsa/statespace/tests/test_collapsed.py::TestTrivariateConventional::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAlternate::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissing::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalPartialMissingAlternate::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAllMissing::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestTrivariateConventionalAllMissingAlternate::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariate::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariateAlternate::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariatePartialMissing::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariatePartialMissingAlternate::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariateAllMissing::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestTrivariateUnivariateAllMissingAlternate::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestDFM::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestDFMClassicalSmoothing::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestDFMUnivariateSmoothing::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestDFMAlternativeSmoothing::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_using_collapsed
tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_smoothed_measurement_disturbance
tsa/statespace/tests/test_collapsed.py::TestDFMMeasurementDisturbance::test_simulation_smoothed_measurement_disturbance
tsa/statespace/tests/test_concentrated.py::test_concentrated_loglike_sarimax
tsa/statespace/tests/test_concentrated.py::test_concentrated_predict_sarimax
tsa/statespace/tests/test_concentrated.py::test_fixed_scale_sarimax
tsa/statespace/tests/test_concentrated.py::test_concentrated_scale_conventional
tsa/statespace/tests/test_concentrated.py::test_concentrated_scale_univariate
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-True-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-False-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-True-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-False-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-True-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-False-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-True-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-False-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-True-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-False-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-True-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-False-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-True-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-False-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-True-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-False-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate[True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate[True-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate[False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate[False-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate_extra[True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate_extra[True-True-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate_extra[True-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate_extra[True-False-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate_extra[False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate_extra[False-True-False]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate_extra[False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate_extra[False-False-False]
tsa/statespace/tests/test_conserve_memory.py::test_fit
tsa/statespace/tests/test_conserve_memory.py::test_low_memory_filter
tsa/statespace/tests/test_conserve_memory.py::test_low_memory_fit
tsa/statespace/tests/test_conserve_memory.py::test_fittedvalues_resid_predict[510]
tsa/statespace/tests/test_conserve_memory.py::test_fittedvalues_resid_predict[2]
tsa/statespace/tests/test_conserve_memory.py::test_get_prediction_memory_conserve
tsa/statespace/tests/test_conserve_memory.py::test_invalid_fittedvalues_resid_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_params
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor::test_dynamic_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_params
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor2::test_dynamic_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_params
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_dynamic_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_params
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_dynamic_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_params
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_general_errors::test_dynamic_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_params
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_ar2_errors::test_dynamic_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_params
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_predict
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_scalar_error::test_dynamic_predict
tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_params
tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_predict
tsa/statespace/tests/test_dynamic_factor.py::TestStaticFactor::test_dynamic_predict
tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_params
tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_predict
tsa/statespace/tests/test_dynamic_factor.py::TestSUR::test_dynamic_predict
tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_params
tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_predict
tsa/statespace/tests/test_dynamic_factor.py::TestSUR_autocorrelated_errors::test_dynamic_predict
tsa/statespace/tests/test_dynamic_factor.py::test_miscellaneous
tsa/statespace/tests/test_dynamic_factor.py::test_predict_custom_index
tsa/statespace/tests/test_dynamic_factor.py::test_forecast_exog
tsa/statespace/tests/test_dynamic_factor.py::test_recreate_model
tsa/statespace/tests/test_dynamic_factor.py::test_append_results
tsa/statespace/tests/test_dynamic_factor.py::test_extend_results
tsa/statespace/tests/test_dynamic_factor.py::test_apply_results
tsa/statespace/tests/test_dynamic_factor.py::test_start_params_nans
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLevelAnalytic::test_results
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLevelAnalyticDirect::test_results
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLinearTrendAnalytic::test_results
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLinearTrendAnalyticDirect::test_results
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLinearTrendAnalyticMissing::test_results
tsa/statespace/tests/test_exact_diffuse_filtering.py::test_common_level_analytic
tsa/statespace/tests/test_exact_diffuse_filtering.py::test_common_level_restricted_analytic
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_forecasts
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_forecasts
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_forecasts
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_forecasts
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_forecasts
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_forecasts
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_forecasts
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_forecasts
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_forecasts
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_forecasts
tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_forecasts
tsa/statespace/tests/test_exact_diffuse_filtering.py::test_irrelevant_state
tsa/statespace/tests/test_exact_diffuse_filtering.py::test_nondiagonal_obs_cov
tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendETSEstimated::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestSESKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestSESHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::test_concentrated_initialization
tsa/statespace/tests/test_exponential_smoothing.py::TestSESConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestMultiIndex::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::test_invalid
tsa/statespace/tests/test_fixed_params.py::test_fix_params
tsa/statespace/tests/test_fixed_params.py::test_results_append
tsa/statespace/tests/test_fixed_params.py::test_results_extend
tsa/statespace/tests/test_fixed_params.py::test_results_apply
tsa/statespace/tests/test_fixed_params.py::test_sarimax_invalid
tsa/statespace/tests/test_fixed_params.py::test_structural_invalid
tsa/statespace/tests/test_fixed_params.py::test_dynamic_factor_invalid
tsa/statespace/tests/test_fixed_params.py::test_varmax_invalid
tsa/statespace/tests/test_fixed_params.py::test_sarimax_nonconsecutive
tsa/statespace/tests/test_fixed_params.py::test_structural
tsa/statespace/tests/test_fixed_params.py::test_dynamic_factor_diag_error_cov
tsa/statespace/tests/test_fixed_params.py::test_score_shape
tsa/statespace/tests/test_impulse_responses.py::test_sarimax
tsa/statespace/tests/test_impulse_responses.py::test_structural
tsa/statespace/tests/test_impulse_responses.py::test_structural
tsa/statespace/tests/test_impulse_responses.py::test_structural
tsa/statespace/tests/test_impulse_responses.py::test_varmax
tsa/statespace/tests/test_impulse_responses.py::test_varmax
tsa/statespace/tests/test_impulse_responses.py::test_varmax
tsa/statespace/tests/test_impulse_responses.py::test_varmax
tsa/statespace/tests/test_impulse_responses.py::test_dynamic_factor
tsa/statespace/tests/test_impulse_responses.py::test_time_varying_ssm
tsa/statespace/tests/test_impulse_responses.py::test_time_varying_in_sample
tsa/statespace/tests/test_impulse_responses.py::test_time_varying_out_of_sample
tsa/statespace/tests/test_impulse_responses.py::test_time_varying_in_sample_anchored
tsa/statespace/tests/test_impulse_responses.py::test_time_varying_out_of_sample_anchored
tsa/statespace/tests/test_impulse_responses.py::test_time_varying_out_of_sample_anchored_end
tsa/statespace/tests/test_impulse_responses.py::test_pandas_univariate_rangeindex
tsa/statespace/tests/test_impulse_responses.py::test_pandas_univariate_dateindex
tsa/statespace/tests/test_impulse_responses.py::test_pandas_multivariate_rangeindex
tsa/statespace/tests/test_impulse_responses.py::test_pandas_multivariate_dateindex
tsa/statespace/tests/test_impulse_responses.py::test_pandas_anchor
tsa/statespace/tests/test_initialization.py::test_global_known
tsa/statespace/tests/test_initialization.py::test_global_diffuse
tsa/statespace/tests/test_initialization.py::test_global_approximate_diffuse
tsa/statespace/tests/test_initialization.py::test_global_stationary
tsa/statespace/tests/test_initialization.py::test_mixed_basic
tsa/statespace/tests/test_initialization.py::test_mixed_stationary
tsa/statespace/tests/test_initialization.py::test_nested
tsa/statespace/tests/test_kalman.py::test_stationary_initialization
tsa/statespace/tests/test_mlemodel.py::test_init_matrices_time_invariant
tsa/statespace/tests/test_mlemodel.py::test_init_matrices_time_varying
tsa/statespace/tests/test_mlemodel.py::test_wrapping
tsa/statespace/tests/test_mlemodel.py::test_fit_misc
tsa/statespace/tests/test_mlemodel.py::test_fit_misc
tsa/statespace/tests/test_mlemodel.py::test_score_misc
tsa/statespace/tests/test_mlemodel.py::test_score_analytic_ar1
tsa/statespace/tests/test_mlemodel.py::test_cov_params
tsa/statespace/tests/test_mlemodel.py::test_transform
tsa/statespace/tests/test_mlemodel.py::test_filter
tsa/statespace/tests/test_mlemodel.py::test_params
tsa/statespace/tests/test_mlemodel.py::test_results
tsa/statespace/tests/test_mlemodel.py::test_results
tsa/statespace/tests/test_mlemodel.py::test_predict
tsa/statespace/tests/test_mlemodel.py::test_forecast
tsa/statespace/tests/test_mlemodel.py::test_summary
tsa/statespace/tests/test_mlemodel.py::test_basic_endog
tsa/statespace/tests/test_mlemodel.py::test_numpy_endog
tsa/statespace/tests/test_mlemodel.py::test_pandas_endog
tsa/statespace/tests/test_mlemodel.py::test_pandas_endog
tsa/statespace/tests/test_mlemodel.py::test_pandas_endog
tsa/statespace/tests/test_mlemodel.py::test_pandas_endog
tsa/statespace/tests/test_mlemodel.py::test_pandas_endog
tsa/statespace/tests/test_mlemodel.py::test_pandas_endog
tsa/statespace/tests/test_mlemodel.py::test_diagnostics
tsa/statespace/tests/test_mlemodel.py::test_diagnostics_nile_eviews
tsa/statespace/tests/test_mlemodel.py::test_diagnostics_nile_durbinkoopman
tsa/statespace/tests/test_mlemodel.py::test_prediction_results
tsa/statespace/tests/test_mlemodel.py::test_lutkepohl_information_criteria
tsa/statespace/tests/test_mlemodel.py::test_append_extend_apply_invalid
tsa/statespace/tests/test_mlemodel.py::test_integer_params
tsa/statespace/tests/test_models.py::TestIntercepts::test_loglike
tsa/statespace/tests/test_models.py::test_large_kposdef
tsa/statespace/tests/test_options.py::TestOptions::test_filter_methods
tsa/statespace/tests/test_pickle.py::test_pickle_fit_sarimax
tsa/statespace/tests/test_pickle.py::test_unobserved_components_pickle
tsa/statespace/tests/test_pickle.py::test_kalman_filter_pickle
tsa/statespace/tests/test_pickle.py::test_representation_pickle
tsa/statespace/tests/test_prediction.py::test_predict_dates
tsa/statespace/tests/test_prediction.py::test_memory_no_predicted
tsa/statespace/tests/test_representation.py::TestClark1987Double::test_loglike
tsa/statespace/tests/test_representation.py::TestClark1987DoubleComplex::test_loglike
tsa/statespace/tests/test_representation.py::TestClark1987Conserve::test_loglike
tsa/statespace/tests/test_representation.py::TestClark1987ForecastDouble::test_loglike
tsa/statespace/tests/test_representation.py::TestClark1987ForecastDoubleComplex::test_loglike
tsa/statespace/tests/test_representation.py::TestClark1987ForecastConserve::test_loglike
tsa/statespace/tests/test_representation.py::TestClark1987ConserveAll::test_loglike
tsa/statespace/tests/test_representation.py::TestClark1989::test_loglike
tsa/statespace/tests/test_representation.py::TestClark1989Conserve::test_loglike
tsa/statespace/tests/test_representation.py::TestClark1989ForecastDouble::test_loglike
tsa/statespace/tests/test_representation.py::TestClark1989ForecastDoubleComplex::test_loglike
tsa/statespace/tests/test_representation.py::TestClark1989ForecastConserve::test_loglike
tsa/statespace/tests/test_representation.py::TestClark1989ConserveAll::test_loglike
tsa/statespace/tests/test_representation.py::TestClark1989PartialMissing::test_loglike
tsa/statespace/tests/test_representation.py::test_slice_notation
tsa/statespace/tests/test_representation.py::test_representation
tsa/statespace/tests/test_representation.py::test_bind
tsa/statespace/tests/test_representation.py::test_initialization
tsa/statespace/tests/test_representation.py::test_init_matrices_time_invariant
tsa/statespace/tests/test_representation.py::test_init_matrices_time_varying
tsa/statespace/tests/test_representation.py::test_no_endog
tsa/statespace/tests/test_representation.py::test_cython
tsa/statespace/tests/test_representation.py::test_filter
tsa/statespace/tests/test_representation.py::test_loglike
tsa/statespace/tests/test_representation.py::test_predict
tsa/statespace/tests/test_representation.py::test_predict
tsa/statespace/tests/test_representation.py::test_predict
tsa/statespace/tests/test_representation.py::test_standardized_forecasts_error
tsa/statespace/tests/test_representation.py::test_simulate
tsa/statespace/tests/test_representation.py::test_impulse_responses
tsa/statespace/tests/test_representation.py::test_missing
tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_loglike
tsa/statespace/tests/test_sarimax.py::TestRealGDPARStata::test_filtered_state
tsa/statespace/tests/test_sarimax.py::TestARIMAStationary::test_loglike
tsa/statespace/tests/test_sarimax.py::TestARIMADiffuse::test_loglike
tsa/statespace/tests/test_sarimax.py::TestAdditiveSeasonal::test_loglike
tsa/statespace/tests/test_sarimax.py::TestAirlineHamilton::test_loglike
tsa/statespace/tests/test_sarimax.py::TestAirlineHarvey::test_loglike
tsa/statespace/tests/test_sarimax.py::TestAirlineStateDifferencing::test_loglike
tsa/statespace/tests/test_sarimax.py::TestFriedmanMLERegression::test_loglike
tsa/statespace/tests/test_sarimax.py::TestFriedmanStateRegression::test_hqic
tsa/statespace/tests/test_sarimax.py::TestFriedmanPredict::test_hqic
tsa/statespace/tests/test_sarimax.py::TestFriedmanPredict::test_dynamic_predict
tsa/statespace/tests/test_sarimax.py::TestFriedmanForecast::test_hqic
tsa/statespace/tests/test_sarimax.py::TestFriedmanForecast::test_forecast
tsa/statespace/tests/test_sarimax.py::TestFriedmanForecast::test_dynamic_forecast
tsa/statespace/tests/test_sarimax.py::Test_ar::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ar::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ar::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ar_as_polynomial::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ar_as_polynomial::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ar_as_polynomial::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ar_trend_c::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ar_trend_ct::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ar_trend_polynomial::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ar_trend_polynomial::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ar_trend_polynomial::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ar_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ar_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ar_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ar_seasonal_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ar_seasonal_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ar_seasonal_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ar_diffuse::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ar_diffuse::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ar_diffuse::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ar_no_enforce::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ar_no_enforce::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ar_no_enforce::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous_in_state::test_start_params
tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous_in_state::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ar_exogenous_in_state::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ma::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ma::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ma::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ma_as_polynomial::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ma_as_polynomial::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ma_as_polynomial::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ma_trend_c::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ma_trend_c::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ma_trend_c::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ma_trend_ct::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ma_trend_ct::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ma_trend_ct::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ma_trend_polynomial::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ma_trend_polynomial::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ma_trend_polynomial::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ma_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ma_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ma_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ma_seasonal_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ma_seasonal_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ma_seasonal_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ma_diffuse::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ma_diffuse::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ma_diffuse::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_ma_exogenous::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_ma_exogenous::test_predict
tsa/statespace/tests/test_sarimax.py::Test_ma_exogenous::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_arma::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_arma::test_predict
tsa/statespace/tests/test_sarimax.py::Test_arma::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_arma_trend_c::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_arma_trend_c::test_predict
tsa/statespace/tests/test_sarimax.py::Test_arma_trend_c::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_arma_trend_ct::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_arma_trend_ct::test_predict
tsa/statespace/tests/test_sarimax.py::Test_arma_trend_ct::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_arma_trend_polynomial::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_arma_trend_polynomial::test_predict
tsa/statespace/tests/test_sarimax.py::Test_arma_trend_polynomial::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_arma_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_arma_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_arma_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_arma_seasonal_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_arma_seasonal_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_arma_seasonal_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_arma_diff_seasonal_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_arma_diff_seasonal_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_arma_diff_seasonal_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_arma_diffuse::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_arma_diffuse::test_predict
tsa/statespace/tests/test_sarimax.py::Test_arma_diffuse::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_arma_exogenous::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_arma_exogenous::test_predict
tsa/statespace/tests/test_sarimax.py::Test_arma_exogenous::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_as_polynomial::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_as_polynomial::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_as_polynomial::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_c::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_c::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_c::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_ct::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_ct::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_ct::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_polynomial::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_polynomial::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_trend_polynomial::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_seasonal_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_seasonal_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_seasonal_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_diffuse::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_diffuse::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_diffuse::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_exogenous::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_exogenous::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ar_exogenous::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_as_polynomial::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_as_polynomial::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_as_polynomial::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_c::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_c::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_c::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_ct::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_ct::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_ct::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_polynomial::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_polynomial::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_trend_polynomial::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_seasonal_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_seasonal_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_seasonal_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_diffuse::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_diffuse::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_diffuse::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_exogenous::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_exogenous::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_ma_exogenous::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_c::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_c::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_c::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_ct::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_ct::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_ct::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_polynomial::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_polynomial::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_trend_polynomial::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_seasonal_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_seasonal_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_seasonal_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diff_seasonal_diff::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diff_seasonal_diff::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diff_seasonal_diff::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diffuse::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diffuse::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_diffuse::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_exogenous::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_exogenous::test_predict
tsa/statespace/tests/test_sarimax.py::Test_seasonal_arma_exogenous::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous::test_predict
tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous_not_hamilton::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous_not_hamilton::test_predict
tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous_not_hamilton::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous_diffuse::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous_diffuse::test_predict
tsa/statespace/tests/test_sarimax.py::Test_sarimax_exogenous_diffuse::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::Test_arma_exog_trend_polynomial_missing::test_loglike
tsa/statespace/tests/test_sarimax.py::Test_arma_exog_trend_polynomial_missing::test_predict
tsa/statespace/tests/test_sarimax.py::Test_arma_exog_trend_polynomial_missing::test_init_keys_replicate
tsa/statespace/tests/test_sarimax.py::test_simple_time_varying
tsa/statespace/tests/test_sarimax.py::test_manual_stationary_initialization
tsa/statespace/tests/test_sarimax.py::test_manual_approximate_diffuse_initialization
tsa/statespace/tests/test_sarimax.py::test_results
tsa/statespace/tests/test_sarimax.py::test_misc_exog
tsa/statespace/tests/test_sarimax.py::test_datasets
tsa/statespace/tests/test_sarimax.py::test_predict_custom_index
tsa/statespace/tests/test_sarimax.py::test_arima000
tsa/statespace/tests/test_sarimax.py::test_concentrated_scale
tsa/statespace/tests/test_sarimax.py::test_forecast_exog
tsa/statespace/tests/test_sarimax.py::test_recreate_model
tsa/statespace/tests/test_sarimax.py::test_append_results
tsa/statespace/tests/test_sarimax.py::test_extend_results
tsa/statespace/tests/test_sarimax.py::test_apply_results
tsa/statespace/tests/test_sarimax.py::test_start_params_small_nobs
tsa/statespace/tests/test_sarimax.py::test_start_params_small_nobs
tsa/statespace/tests/test_sarimax.py::test_simple_differencing_int64index
tsa/statespace/tests/test_sarimax.py::test_simple_differencing_rangeindex
tsa/statespace/tests/test_sarimax.py::test_simple_differencing_dateindex
tsa/statespace/tests/test_save.py::test_sarimax
tsa/statespace/tests/test_save.py::test_sarimax_pickle
tsa/statespace/tests/test_save.py::test_structural
tsa/statespace/tests/test_save.py::test_structural_pickle
tsa/statespace/tests/test_save.py::test_dynamic_factor
tsa/statespace/tests/test_save.py::test_dynamic_factor_pickle
tsa/statespace/tests/test_save.py::test_varmax
tsa/statespace/tests/test_save.py::test_varmax_pickle
tsa/statespace/tests/test_simulate.py::test_arma_lfilter
tsa/statespace/tests/test_simulate.py::test_arma_direct
tsa/statespace/tests/test_simulate.py::test_structural
tsa/statespace/tests/test_simulate.py::test_structural
tsa/statespace/tests/test_simulate.py::test_structural
tsa/statespace/tests/test_simulate.py::test_varmax
tsa/statespace/tests/test_simulate.py::test_varmax
tsa/statespace/tests/test_simulate.py::test_varmax
tsa/statespace/tests/test_simulate.py::test_varmax
tsa/statespace/tests/test_simulate.py::test_dynamic_factor
tsa/statespace/tests/test_simulate.py::test_known_initialization
tsa/statespace/tests/test_simulate.py::test_sequential_simulate
tsa/statespace/tests/test_simulate.py::test_sarimax_end_time_invariant_noshocks
tsa/statespace/tests/test_simulate.py::test_sarimax_simple_differencing_end_time_invariant_noshocks
tsa/statespace/tests/test_simulate.py::test_sarimax_time_invariant_shocks
tsa/statespace/tests/test_simulate.py::test_sarimax_simple_differencing_end_time_invariant_shocks
tsa/statespace/tests/test_simulate.py::test_sarimax_time_varying_trend_noshocks
tsa/statespace/tests/test_simulate.py::test_sarimax_simple_differencing_time_varying_trend_noshocks
tsa/statespace/tests/test_simulate.py::test_sarimax_time_varying_trend_shocks
tsa/statespace/tests/test_simulate.py::test_sarimax_simple_differencing_time_varying_trend_shocks
tsa/statespace/tests/test_simulate.py::test_sarimax_time_varying_exog_noshocks
tsa/statespace/tests/test_simulate.py::test_sarimax_simple_differencing_time_varying_exog_noshocks
tsa/statespace/tests/test_simulate.py::test_sarimax_time_varying_exog_shocks
tsa/statespace/tests/test_simulate.py::test_sarimax_simple_differencing_time_varying_exog_shocks
tsa/statespace/tests/test_simulate.py::test_unobserved_components_end_time_invariant_noshocks
tsa/statespace/tests/test_simulate.py::test_unobserved_components_end_time_invariant_shocks
tsa/statespace/tests/test_simulate.py::test_unobserved_components_end_time_varying_exog_noshocks
tsa/statespace/tests/test_simulate.py::test_unobserved_components_end_time_varying_exog_shocks
tsa/statespace/tests/test_simulate.py::test_varmax_end_time_invariant_noshocks
tsa/statespace/tests/test_simulate.py::test_varmax_end_time_invariant_shocks
tsa/statespace/tests/test_simulate.py::test_varmax_end_time_varying_trend_noshocks
tsa/statespace/tests/test_simulate.py::test_varmax_end_time_varying_trend_shocks
tsa/statespace/tests/test_simulate.py::test_varmax_end_time_varying_exog_noshocks
tsa/statespace/tests/test_simulate.py::test_varmax_end_time_varying_exog_shocks
tsa/statespace/tests/test_simulate.py::test_dynamic_factor_end_time_invariant_noshocks
tsa/statespace/tests/test_simulate.py::test_dynamic_factor_end_time_invariant_shocks
tsa/statespace/tests/test_simulate.py::test_dynamic_factor_end_time_varying_exog_noshocks
tsa/statespace/tests/test_simulate.py::test_dynamic_factor_end_time_varying_exog_shocks
tsa/statespace/tests/test_simulate.py::test_pandas_univariate_rangeindex
tsa/statespace/tests/test_simulate.py::test_pandas_univariate_rangeindex_repetitions
tsa/statespace/tests/test_simulate.py::test_pandas_univariate_dateindex
tsa/statespace/tests/test_simulate.py::test_pandas_univariate_dateindex_repetitions
tsa/statespace/tests/test_simulate.py::test_pandas_multivariate_rangeindex
tsa/statespace/tests/test_simulate.py::test_pandas_multivariate_rangeindex_repetitions
tsa/statespace/tests/test_simulate.py::test_pandas_multivariate_dateindex
tsa/statespace/tests/test_simulate.py::test_pandas_multivariate_dateindex_repetitions
tsa/statespace/tests/test_simulate.py::test_pandas_anchor
tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnown::test_loglike
tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnown::test_simulation_smoothing_1
tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnown::test_simulation_smoothing_2
tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingAll::test_loglike
tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingAll::test_simulation_smoothing_1
tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingAll::test_simulation_smoothing_2
tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingPartial::test_loglike
tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingPartial::test_simulation_smoothing_1
tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingPartial::test_simulation_smoothing_2
tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingMixed::test_loglike
tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingMixed::test_simulation_smoothing_1
tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVARKnownMissingMixed::test_simulation_smoothing_2
tsa/statespace/tests/test_simulation_smoothing.py::TestDFM::test_simulate_0
tsa/statespace/tests/test_simulation_smoothing.py::TestDFM::test_simulation_smoothing_1
tsa/statespace/tests/test_simulation_smoothing.py::TestDFM::test_simulation_smoothing_2
tsa/statespace/tests/test_simulation_smoothing.py::TestMultivariateVAR::test_loglike
tsa/statespace/tests/test_simulation_smoothing.py::test_misc
tsa/statespace/tests/test_simulation_smoothing.py::test_simulation_smoothing_obs_intercept
tsa/statespace/tests/test_simulation_smoothing.py::test_simulation_smoothing_state_intercept
tsa/statespace/tests/test_simulation_smoothing.py::test_simulation_smoothing_state_intercept_diffuse
tsa/statespace/tests/test_smoothing.py::TestStatesAR3::test_predict_obs
tsa/statespace/tests/test_smoothing.py::TestStatesAR3AlternateTiming::test_predict_obs
tsa/statespace/tests/test_smoothing.py::TestStatesAR3AlternativeSmoothing::test_predict_obs
tsa/statespace/tests/test_smoothing.py::TestStatesAR3UnivariateSmoothing::test_predict_obs
tsa/statespace/tests/test_smoothing.py::TestStatesMissingAR3::test_predicted_states
tsa/statespace/tests/test_smoothing.py::TestStatesMissingAR3AlternateTiming::test_predicted_states
tsa/statespace/tests/test_smoothing.py::TestStatesMissingAR3AlternativeSmoothing::test_predicted_states
tsa/statespace/tests/test_smoothing.py::TestStatesMissingAR3UnivariateSmoothing::test_predicted_states
tsa/statespace/tests/test_smoothing.py::TestMultivariateMissing::test_loglike
tsa/statespace/tests/test_smoothing.py::TestMultivariateMissingClassicalSmoothing::test_loglike
tsa/statespace/tests/test_smoothing.py::TestMultivariateMissingAlternativeSmoothing::test_loglike
tsa/statespace/tests/test_smoothing.py::TestMultivariateMissingUnivariateSmoothing::test_loglike
tsa/statespace/tests/test_smoothing.py::TestMultivariateVAR::test_loglike
tsa/statespace/tests/test_smoothing.py::TestMultivariateVARAlternativeSmoothing::test_loglike
tsa/statespace/tests/test_smoothing.py::TestMultivariateVARClassicalSmoothing::test_loglike
tsa/statespace/tests/test_smoothing.py::TestMultivariateVARUnivariate::test_loglike
tsa/statespace/tests/test_smoothing.py::TestMultivariateVARUnivariateSmoothing::test_loglike
tsa/statespace/tests/test_smoothing.py::TestVARAutocovariances::test_smoothed_state_autocov
tsa/statespace/tests/test_smoothing.py::TestVARAutocovariancesAlternativeSmoothing::test_smoothed_state_autocov
tsa/statespace/tests/test_smoothing.py::TestVARAutocovariancesClassicalSmoothing::test_smoothed_state_autocov
tsa/statespace/tests/test_smoothing.py::TestVARAutocovariancesUnivariateSmoothing::test_smoothed_state_autocov
tsa/statespace/tests/test_structural.py::test_irregular
tsa/statespace/tests/test_structural.py::test_irregular
tsa/statespace/tests/test_structural.py::test_irregular
tsa/statespace/tests/test_structural.py::test_irregular
tsa/statespace/tests/test_structural.py::test_irregular
tsa/statespace/tests/test_structural.py::test_irregular
tsa/statespace/tests/test_structural.py::test_deterministic_constant
tsa/statespace/tests/test_structural.py::test_deterministic_constant
tsa/statespace/tests/test_structural.py::test_deterministic_constant
tsa/statespace/tests/test_structural.py::test_deterministic_constant
tsa/statespace/tests/test_structural.py::test_deterministic_constant
tsa/statespace/tests/test_structural.py::test_deterministic_constant
tsa/statespace/tests/test_structural.py::test_random_walk
tsa/statespace/tests/test_structural.py::test_random_walk
tsa/statespace/tests/test_structural.py::test_random_walk
tsa/statespace/tests/test_structural.py::test_random_walk
tsa/statespace/tests/test_structural.py::test_random_walk
tsa/statespace/tests/test_structural.py::test_random_walk
tsa/statespace/tests/test_structural.py::test_local_level
tsa/statespace/tests/test_structural.py::test_local_level
tsa/statespace/tests/test_structural.py::test_local_level
tsa/statespace/tests/test_structural.py::test_local_level
tsa/statespace/tests/test_structural.py::test_local_level
tsa/statespace/tests/test_structural.py::test_local_level
tsa/statespace/tests/test_structural.py::test_deterministic_trend
tsa/statespace/tests/test_structural.py::test_deterministic_trend
tsa/statespace/tests/test_structural.py::test_deterministic_trend
tsa/statespace/tests/test_structural.py::test_deterministic_trend
tsa/statespace/tests/test_structural.py::test_deterministic_trend
tsa/statespace/tests/test_structural.py::test_deterministic_trend
tsa/statespace/tests/test_structural.py::test_random_walk_with_drift
tsa/statespace/tests/test_structural.py::test_random_walk_with_drift
tsa/statespace/tests/test_structural.py::test_random_walk_with_drift
tsa/statespace/tests/test_structural.py::test_random_walk_with_drift
tsa/statespace/tests/test_structural.py::test_random_walk_with_drift
tsa/statespace/tests/test_structural.py::test_random_walk_with_drift
tsa/statespace/tests/test_structural.py::test_local_linear_deterministic_trend
tsa/statespace/tests/test_structural.py::test_local_linear_deterministic_trend
tsa/statespace/tests/test_structural.py::test_local_linear_deterministic_trend
tsa/statespace/tests/test_structural.py::test_local_linear_deterministic_trend
tsa/statespace/tests/test_structural.py::test_local_linear_deterministic_trend
tsa/statespace/tests/test_structural.py::test_local_linear_deterministic_trend
tsa/statespace/tests/test_structural.py::test_local_linear_trend
tsa/statespace/tests/test_structural.py::test_local_linear_trend
tsa/statespace/tests/test_structural.py::test_local_linear_trend
tsa/statespace/tests/test_structural.py::test_local_linear_trend
tsa/statespace/tests/test_structural.py::test_local_linear_trend
tsa/statespace/tests/test_structural.py::test_local_linear_trend
tsa/statespace/tests/test_structural.py::test_smooth_trend
tsa/statespace/tests/test_structural.py::test_smooth_trend
tsa/statespace/tests/test_structural.py::test_smooth_trend
tsa/statespace/tests/test_structural.py::test_smooth_trend
tsa/statespace/tests/test_structural.py::test_smooth_trend
tsa/statespace/tests/test_structural.py::test_smooth_trend
tsa/statespace/tests/test_structural.py::test_random_trend
tsa/statespace/tests/test_structural.py::test_random_trend
tsa/statespace/tests/test_structural.py::test_random_trend
tsa/statespace/tests/test_structural.py::test_random_trend
tsa/statespace/tests/test_structural.py::test_random_trend
tsa/statespace/tests/test_structural.py::test_random_trend
tsa/statespace/tests/test_structural.py::test_cycle
tsa/statespace/tests/test_structural.py::test_cycle
tsa/statespace/tests/test_structural.py::test_seasonal
tsa/statespace/tests/test_structural.py::test_seasonal
tsa/statespace/tests/test_structural.py::test_freq_seasonal
tsa/statespace/tests/test_structural.py::test_freq_seasonal
tsa/statespace/tests/test_structural.py::test_reg
tsa/statespace/tests/test_structural.py::test_reg
tsa/statespace/tests/test_structural.py::test_reg
tsa/statespace/tests/test_structural.py::test_reg
tsa/statespace/tests/test_structural.py::test_reg
tsa/statespace/tests/test_structural.py::test_reg
tsa/statespace/tests/test_structural.py::test_reg
tsa/statespace/tests/test_structural.py::test_reg
tsa/statespace/tests/test_structural.py::test_rtrend_ar1
tsa/statespace/tests/test_structural.py::test_rtrend_ar1
tsa/statespace/tests/test_structural.py::test_rtrend_ar1
tsa/statespace/tests/test_structural.py::test_rtrend_ar1
tsa/statespace/tests/test_structural.py::test_rtrend_ar1
tsa/statespace/tests/test_structural.py::test_rtrend_ar1
tsa/statespace/tests/test_structural.py::test_lltrend_cycle_seasonal_reg_ar1
tsa/statespace/tests/test_structural.py::test_lltrend_cycle_seasonal_reg_ar1
tsa/statespace/tests/test_structural.py::test_lltrend_cycle_seasonal_reg_ar1
tsa/statespace/tests/test_structural.py::test_lltrend_cycle_seasonal_reg_ar1
tsa/statespace/tests/test_structural.py::test_lltrend_cycle_seasonal_reg_ar1
tsa/statespace/tests/test_structural.py::test_lltrend_cycle_seasonal_reg_ar1
tsa/statespace/tests/test_structural.py::test_lltrend_cycle_seasonal_reg_ar1
tsa/statespace/tests/test_structural.py::test_lltrend_cycle_seasonal_reg_ar1
tsa/statespace/tests/test_structural.py::test_lltrend_cycle_seasonal_reg_ar1
tsa/statespace/tests/test_structural.py::test_start_params
tsa/statespace/tests/test_structural.py::test_forecast
tsa/statespace/tests/test_structural.py::test_misc_exog
tsa/statespace/tests/test_structural.py::test_predict_custom_index
tsa/statespace/tests/test_structural.py::test_matrices_somewhat_complicated_model
tsa/statespace/tests/test_structural.py::test_forecast_exog
tsa/statespace/tests/test_structural.py::test_recreate_model
tsa/statespace/tests/test_structural.py::test_append_results
tsa/statespace/tests/test_structural.py::test_extend_results
tsa/statespace/tests/test_structural.py::test_apply_results
tsa/statespace/tests/test_univariate.py::TestClark1989::test_using_univariate
tsa/statespace/tests/test_univariate.py::TestClark1989Alternate::test_using_univariate
tsa/statespace/tests/test_univariate.py::TestMultivariateGeneralObsCov::test_using_univariate
tsa/statespace/tests/test_univariate.py::TestMultivariateAllMissingGeneralObsCov::test_using_univariate
tsa/statespace/tests/test_univariate.py::TestMultivariatePartialMissingGeneralObsCov::test_using_univariate
tsa/statespace/tests/test_univariate.py::TestMultivariateMixedMissingGeneralObsCov::test_using_univariate
tsa/statespace/tests/test_univariate.py::TestMultivariateVAR::test_forecasts
tsa/statespace/tests/test_univariate.py::test_time_varying_transition
tsa/statespace/tests/test_var.py::test_var_basic
tsa/statespace/tests/test_var.py::test_var_c
tsa/statespace/tests/test_var.py::test_var_ct
tsa/statespace/tests/test_var.py::test_var_ct_as_exog0
tsa/statespace/tests/test_var.py::test_var_ct_as_exog1
tsa/statespace/tests/test_var.py::test_var_ctt
tsa/statespace/tests/test_var.py::test_var_ct_exog
tsa/statespace/tests/test_var.py::test_var_c_2exog
tsa/statespace/tests/test_varmax.py::TestVAR::test_mle
tsa/statespace/tests/test_varmax.py::TestVAR::test_predict
tsa/statespace/tests/test_varmax.py::TestVAR::test_dynamic_predict
tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_mle
tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_predict
tsa/statespace/tests/test_varmax.py::TestVAR_diagonal::test_dynamic_predict
tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_params
tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_predict
tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_dynamic_predict
tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_mle
tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_predict
tsa/statespace/tests/test_varmax.py::TestVAR_obs_intercept::test_dynamic_predict
tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_params
tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_forecast
tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_params
tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_forecast
tsa/statespace/tests/test_varmax.py::TestVAR2::test_mle
tsa/statespace/tests/test_varmax.py::TestVAR2::test_predict
tsa/statespace/tests/test_varmax.py::TestVAR2::test_dynamic_predict
tsa/statespace/tests/test_varmax.py::TestVARMA::test_predict
tsa/statespace/tests/test_varmax.py::TestVARMA::test_dynamic_predict
tsa/statespace/tests/test_varmax.py::TestVMA1::test_predict
tsa/statespace/tests/test_varmax.py::TestVMA1::test_dynamic_predict
tsa/statespace/tests/test_varmax.py::test_specifications
tsa/statespace/tests/test_varmax.py::test_misc_exog
tsa/statespace/tests/test_varmax.py::test_predict_custom_index
tsa/statespace/tests/test_varmax.py::test_forecast_exog
tsa/statespace/tests/test_varmax.py::test_append_results
tsa/statespace/tests/test_varmax.py::test_extend_results
tsa/statespace/tests/test_varmax.py::test_apply_results
tsa/statespace/tests/test_varmax.py::test_vma1_exog
tsa/tests/test_ar.py::test_dynamic_against_sarimax
tsa/tests/test_stattools.py::test_innovations_algo_filter_kalman_filter
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/representation.py:267: UserWarning: Representation/KalmanFilter (and hence much of tsa.statespace) can give wrong results on armhf (armv7) and hppa - https://bugs.debian.org/924036
warnings.warn(warn_kalman)
regression/tests/test_recursive_ls.py::test_multiple_constraints
tsa/statespace/tests/test_sarimax.py::Test_arma::test_results
tsa/statespace/tests/test_sarimax.py::Test_arma_exogenous::test_results
tsa/statespace/tests/test_varmax.py::TestVAR_measurement_error::test_results
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/model.py:1354: RuntimeWarning: invalid value encountered in sqrt
bse_ = np.sqrt(np.diag(self.cov_params()))
robust/tests/test_scale.py::TestMad::test_mad_empty
/usr/lib/python3/dist-packages/numpy/core/fromnumeric.py:3256: RuntimeWarning: Mean of empty slice.
return _methods._mean(a, axis=axis, dtype=dtype,
robust/tests/test_scale.py::TestMad::test_mad_empty
/usr/lib/python3/dist-packages/numpy/core/_methods.py:161: RuntimeWarning: invalid value encountered in double_scalars
ret = ret.dtype.type(ret / rcount)
robust/tests/test_scale.py::TestHuberAxes::test_axis1
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/robust/scale.py:164: RuntimeWarning: divide by zero encountered in true_divide
subset = np.less_equal(np.abs((a - mu)/scale), self.c)
sandbox/distributions/tests/test_extras.py::test_skewt
/usr/lib/python3/dist-packages/scipy/stats/_continuous_distns.py:5261: RuntimeWarning: overflow encountered in double_scalars
Px /= np.sqrt(r*np.pi)*(1+(x**2)/r)**((r+1)/2)
sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_predict
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/sandbox/gam.py:327: IterationLimitWarning:
Maximum iteration reached.
warnings.warn(iteration_limit_doc, IterationLimitWarning)
stats/tests/test_contingency_tables.py::TestStratified1::test_pandas
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/contingency_tables.py:1216: RuntimeWarning: divide by zero encountered in true_divide
v11 = (1 / e11 + 1 / (self._apc - e11) + 1 / (self._apb - e11) +
stats/tests/test_contingency_tables.py::TestStratified1::test_pandas
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/contingency_tables.py:1216: RuntimeWarning: invalid value encountered in add
v11 = (1 / e11 + 1 / (self._apc - e11) + 1 / (self._apb - e11) +
stats/tests/test_contingency_tables.py::TestStratified1::test_pandas
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/contingency_tables.py:1217: RuntimeWarning: divide by zero encountered in true_divide
1 / (self._dma + e11))
stats/tests/test_contingency_tables.py::TestStratified1::test_pandas
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/contingency_tables.py:1220: RuntimeWarning: invalid value encountered in true_divide
statistic = np.sum((table[0, 0, :] - e11)**2 / v11)
stats/tests/test_corrpsd.py::TestCovPSD::test_cov_nearest
stats/tests/test_corrpsd.py::TestCorrPSD1::test_nearest
stats/tests/test_corrpsd.py::test_corrpsd_threshold[0]
stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-15]
stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-10]
stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-06]
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/correlation_tools.py:90: IterationLimitWarning:
Maximum iteration reached.
warnings.warn(iteration_limit_doc, IterationLimitWarning)
stats/tests/test_diagnostic.py::TestDiagnosticG::test_normality
stats/tests/test_diagnostic.py::TestDiagnosticGPandas::test_normality
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/_adnorm.py:70: RuntimeWarning: divide by zero encountered in log1p
s = np.sum((2 * i[sl1] - 1.0) / nobs * (np.log(z) + np.log1p(-z[sl2])),
stats/tests/test_dist_dependant_measures.py::TestDistDependenceMeasures::test_statistic_value_emp_method
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/dist_dependence_measures.py:137: UserWarning: p-value was 0.0 when using the empirical method. The asymptotic approximation will be used instead
warnings.warn(msg)
stats/tests/test_power.py::test_power_solver_warn
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/power.py:89: RuntimeWarning: invalid value encountered in sqrt
pow_ = stats.norm.sf(crit - d*np.sqrt(nobs)/sigma)
stats/tests/test_tost.py::test_tost_asym
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/stats/weightstats.py:1298: RuntimeWarning: invalid value encountered in log
low = transform(low)
tsa/arima/estimators/tests/test_statespace.py::test_basic
tsa/arima/tests/test_model.py::test_low_memory
tsa/statespace/tests/test_concentrated.py::test_concentrated_loglike_sarimax
tsa/statespace/tests/test_concentrated.py::test_concentrated_predict_sarimax
tsa/statespace/tests/test_concentrated.py::test_concentrated_scale_conventional
tsa/statespace/tests/test_concentrated.py::test_concentrated_scale_univariate
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_fit
tsa/statespace/tests/test_conserve_memory.py::test_fittedvalues_resid_predict[510]
tsa/statespace/tests/test_conserve_memory.py::test_fittedvalues_resid_predict[2]
tsa/statespace/tests/test_conserve_memory.py::test_get_prediction_memory_conserve
tsa/statespace/tests/test_conserve_memory.py::test_invalid_fittedvalues_resid_predict
tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestSESKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestSESKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestSESHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::test_concentrated_initialization
tsa/statespace/tests/test_exponential_smoothing.py::TestSESConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestSESConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestMultiIndex::test_fitted
tsa/statespace/tests/test_mlemodel.py::test_append_extend_apply_invalid
tsa/statespace/tests/test_mlemodel.py::test_integer_params
tsa/statespace/tests/test_sarimax.py::test_concentrated_scale
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/kalman_filter.py:1067: RuntimeWarning: invalid value encountered in cdouble_scalars
scale = np.sum(kfilter.scale[d:]) / nobs_k_endog
tsa/arima/estimators/tests/test_statespace.py::test_basic
tsa/arima/tests/test_model.py::test_low_memory
tsa/statespace/tests/test_concentrated.py::test_concentrated_loglike_sarimax
tsa/statespace/tests/test_concentrated.py::test_concentrated_predict_sarimax
tsa/statespace/tests/test_concentrated.py::test_concentrated_scale_conventional
tsa/statespace/tests/test_concentrated.py::test_concentrated_scale_univariate
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_fit
tsa/statespace/tests/test_conserve_memory.py::test_fittedvalues_resid_predict[510]
tsa/statespace/tests/test_conserve_memory.py::test_fittedvalues_resid_predict[2]
tsa/statespace/tests/test_conserve_memory.py::test_get_prediction_memory_conserve
tsa/statespace/tests/test_conserve_memory.py::test_invalid_fittedvalues_resid_predict
tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestSESKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestSESKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestSESHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::test_concentrated_initialization
tsa/statespace/tests/test_exponential_smoothing.py::TestSESConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestSESConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestMultiIndex::test_fitted
tsa/statespace/tests/test_mlemodel.py::test_append_extend_apply_invalid
tsa/statespace/tests/test_mlemodel.py::test_integer_params
tsa/statespace/tests/test_sarimax.py::test_concentrated_scale
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/kalman_filter.py:1082: RuntimeWarning: invalid value encountered in true_divide
scale_obs / scale)
tsa/arima/tests/test_model.py::test_low_memory
tsa/statespace/tests/test_concentrated.py::test_concentrated_loglike_sarimax
tsa/statespace/tests/test_concentrated.py::test_concentrated_predict_sarimax
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_fit
tsa/statespace/tests/test_conserve_memory.py::test_low_memory_filter
tsa/statespace/tests/test_conserve_memory.py::test_low_memory_fit
tsa/statespace/tests/test_conserve_memory.py::test_fittedvalues_resid_predict[510]
tsa/statespace/tests/test_conserve_memory.py::test_fittedvalues_resid_predict[2]
tsa/statespace/tests/test_conserve_memory.py::test_get_prediction_memory_conserve
tsa/statespace/tests/test_conserve_memory.py::test_invalid_fittedvalues_resid_predict
tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_fitted
tsa/statespace/tests/test_exponential_smoothing.py::TestSESKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestSESKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendKnownInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendKnownInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestSESHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendHeuristicInitialization::test_heuristic
tsa/statespace/tests/test_exponential_smoothing.py::test_concentrated_initialization
tsa/statespace/tests/test_exponential_smoothing.py::TestSESConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestSESConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendConcentratedInitialization::test_given_params
tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersNoTrendConcentratedInitialization::test_estimated_params
tsa/statespace/tests/test_exponential_smoothing.py::TestMultiIndex::test_fitted
tsa/statespace/tests/test_mlemodel.py::test_append_extend_apply_invalid
tsa/statespace/tests/test_mlemodel.py::test_integer_params
tsa/statespace/tests/test_pickle.py::test_pickle_fit_sarimax
tsa/statespace/tests/test_sarimax.py::test_concentrated_scale
/usr/lib/python3/dist-packages/numpy/linalg/linalg.py:1881: RuntimeWarning: invalid value encountered in greater
return count_nonzero(S > tol, axis=-1)
tsa/arima/tests/test_model.py::test_low_memory
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-True-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[True-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-True-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_extras[False-False-False-True]
tsa/statespace/tests/test_conserve_memory.py::test_fit
tsa/statespace/tests/test_conserve_memory.py::test_low_memory_filter
tsa/statespace/tests/test_conserve_memory.py::test_low_memory_fit
tsa/statespace/tests/test_conserve_memory.py::test_fittedvalues_resid_predict[510]
tsa/statespace/tests/test_conserve_memory.py::test_get_prediction_memory_conserve
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/kalman_filter.py:998: RuntimeWarning: invalid value encountered in cdouble_scalars
scale = np.sum(kfilter.scale[d:]) / nobs_k_endog
tsa/regime_switching/tests/test_markov_autoregression.py::test_predict
tsa/regime_switching/tests/test_markov_autoregression.py::test_conditional_loglikelihoods
tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR2Short::test_llf
tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR4::test_llf
tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR2Switch::test_llf
tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1Switch::test_llf
tsa/regime_switching/tests/test_markov_autoregression.py::TestHamiltonAR1SwitchTVTP::test_llf
tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardo::test_llf
tsa/regime_switching/tests/test_markov_autoregression.py::TestFilardoPandas::test_llf
tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConst::test_summary
tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstShort::test_summary
tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1::test_summary
tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog::test_summary
tsa/regime_switching/tests/test_markov_regression.py::TestFedFundsConstL1Exog3::test_summary
tsa/regime_switching/tests/test_markov_regression.py::TestAreturnsConstL1Variance::test_summary
tsa/regime_switching/tests/test_markov_regression.py::TestMumpspcNoconstL1Variance::test_summary
tsa/regime_switching/tests/test_markov_regression.py::test_avoid_underflow
tsa/regime_switching/tests/test_markov_regression.py::test_exog_tvtp
tsa/regime_switching/tests/test_markov_switching.py::test_init_endog
tsa/regime_switching/tests/test_markov_switching.py::test_init_exog_tvtp
tsa/regime_switching/tests/test_markov_switching.py::test_transition_matrix
tsa/regime_switching/tests/test_markov_switching.py::test_initial_probabilities
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/regime_switching/markov_switching.py:497: UserWarning: Regime switching models (Markov(Auto)Regression) can give wrong results on armhf (armv7)
warnings.warn(warn_rswitch_platform)
tsa/statespace/tests/test_concentrated.py::test_concentrated_scale_univariate
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate[True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood_multivariate[False-True]
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/kalman_filter.py:900: UserWarning: Positive semi-definite observation covariance matrix encountered at period 0
kfilter()
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-True-True]
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/kalman_filter.py:1081: RuntimeWarning: divide by zero encountered in log
(self.k_endog - nmissing - nsingular) * np.log(scale) +
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-True-True]
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/kalman_filter.py:1081: RuntimeWarning: invalid value encountered in multiply
(self.k_endog - nmissing - nsingular) * np.log(scale) +
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-True-True]
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/kalman_filter.py:1082: RuntimeWarning: divide by zero encountered in true_divide
scale_obs / scale)
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-True-True]
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/kalman_filter.py:1081: RuntimeWarning: invalid value encountered in add
(self.k_endog - nmissing - nsingular) * np.log(scale) +
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-True-True]
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/kalman_filter.py:1010: RuntimeWarning: divide by zero encountered in log
loglike += -0.5 * nobs_k_endog * np.log(scale)
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-True-True]
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/kalman_filter.py:1010: RuntimeWarning: invalid value encountered in multiply
loglike += -0.5 * nobs_k_endog * np.log(scale)
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[True-True-True-True]
tsa/statespace/tests/test_conserve_memory.py::test_memory_no_likelihood[False-True-True-True]
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tools/numdiff.py:241: RuntimeWarning: invalid value encountered in cdouble_scalars
hess[i, j] = (f(*((x + 1j*ee[i, :] + ee[j, :],) + args), **kwargs)
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog1::test_bse_approx
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py:312: RuntimeWarning: invalid value encountered in sqrt
bse = self.results._cov_params_approx().diagonal()**0.5
tsa/statespace/tests/test_dynamic_factor.py::TestDynamicFactor_exog2::test_bse_approx
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor.py:337: RuntimeWarning: invalid value encountered in sqrt
bse = self.results._cov_params_approx().diagonal()**0.5
tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_misc
tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_misc
tsa/statespace/tests/test_exponential_smoothing.py::TestMultiIndex::test_misc
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/mlemodel.py:2885: RuntimeWarning: divide by zero encountered in true_divide
return self.params / self.bse
tsa/statespace/tests/test_mlemodel.py::test_integer_params
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/kalman_filter.py:1758: RuntimeWarning: invalid value encountered in double_scalars
self.scale = np.sum(scale_obs[d:]) / nobs_k_endog
tsa/statespace/tests/test_pickle.py::test_pickle_fit_sarimax
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/base/optimizer.py:299: RuntimeWarning: invalid value encountered in greater
while (iterations < maxiter and np.any(np.abs(newparams -
tsa/statespace/tests/test_sarimax.py::TestSARIMAXStatsmodels::test_bse
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py:81: RuntimeWarning: invalid value encountered in sqrt
bse = cpa.diagonal()**0.5
tsa/statespace/tests/test_sarimax.py::TestARIMAStationary::test_bse_approx
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py:226: RuntimeWarning: invalid value encountered in sqrt
bse = self.result._cov_params_approx(
tsa/statespace/tests/test_sarimax.py::TestARIMADiffuse::test_bse_approx
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py:294: RuntimeWarning: invalid value encountered in sqrt
bse = self.result._cov_params_approx(
tsa/statespace/tests/test_sarimax.py::TestAdditiveSeasonal::test_bse_approx
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py:383: RuntimeWarning: invalid value encountered in sqrt
bse = self.result._cov_params_approx(
tsa/statespace/tests/test_sarimax.py::TestFriedmanMLERegression::test_bse_approx
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py:696: RuntimeWarning: invalid value encountered in sqrt
bse = self.result._cov_params_approx(
tsa/statespace/tests/test_sarimax.py::TestFriedmanStateRegression::test_bse_approx
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/tests/test_sarimax.py:810: RuntimeWarning: invalid value encountered in sqrt
bse = self.result._cov_params_approx(
tsa/statespace/tests/test_varmax.py::TestVAR_exog::test_predict
tsa/statespace/tests/test_varmax.py::TestVAR_exog2::test_predict
tsa/statespace/tests/test_varmax.py::test_misc_exog
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/statespace/mlemodel.py:1728: ValueWarning: Exogenous array provided, but additional data is not required. `exog` argument ignored.
warnings.warn('Exogenous array provided, but additional data'
tsa/tests/test_ar.py::test_parameterless_autoreg
tsa/tests/test_ar.py::test_parameterless_autoreg
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/ar_model.py:1919: FutureWarning: the 'maxlag' keyword is deprecated, use 'nlags' instead
res = het_arch(self.resid, maxlag=lag, autolag=None)
tsa/tests/test_holtwinters.py::TestHoltWinters::test_predict
tsa/tests/test_holtwinters.py::TestHoltWinters::test_ndarray
tsa/tests/test_holtwinters.py::TestHoltWinters::test_forecast
tsa/tests/test_holtwinters.py::TestHoltWinters::test_hw_seasonal
tsa/tests/test_holtwinters.py::TestHoltWinters::test_hw_seasonal_buggy
tsa/tests/test_holtwinters.py::test_start_params[add-add]
tsa/tests/test_holtwinters.py::test_start_params[add-mul]
tsa/tests/test_holtwinters.py::test_start_params[add-None]
tsa/tests/test_holtwinters.py::test_start_params[mul-add]
tsa/tests/test_holtwinters.py::test_start_params[mul-mul]
tsa/tests/test_holtwinters.py::test_start_params[mul-None]
tsa/tests/test_holtwinters.py::test_start_params[None-add]
tsa/tests/test_holtwinters.py::test_start_params[None-mul]
tsa/tests/test_holtwinters.py::test_start_params[None-None]
tsa/tests/test_holtwinters.py::test_float_boxcox[add-add]
tsa/tests/test_holtwinters.py::test_float_boxcox[add-mul]
tsa/tests/test_holtwinters.py::test_float_boxcox[add-None]
tsa/tests/test_holtwinters.py::test_float_boxcox[mul-add]
tsa/tests/test_holtwinters.py::test_float_boxcox[mul-mul]
tsa/tests/test_holtwinters.py::test_float_boxcox[mul-None]
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/holtwinters.py:725: RuntimeWarning: invalid value encountered in less_equal
loc = initial_p <= lb
tsa/tests/test_holtwinters.py::TestHoltWinters::test_predict
tsa/tests/test_holtwinters.py::TestHoltWinters::test_ndarray
tsa/tests/test_holtwinters.py::TestHoltWinters::test_forecast
tsa/tests/test_holtwinters.py::TestHoltWinters::test_simple_exp_smoothing
tsa/tests/test_holtwinters.py::TestHoltWinters::test_holt
tsa/tests/test_holtwinters.py::TestHoltWinters::test_holt_damp_fit
tsa/tests/test_holtwinters.py::TestHoltWinters::test_hw_seasonal
tsa/tests/test_holtwinters.py::TestHoltWinters::test_hw_seasonal_buggy
tsa/tests/test_holtwinters.py::test_start_params[add-add]
tsa/tests/test_holtwinters.py::test_start_params[add-mul]
tsa/tests/test_holtwinters.py::test_start_params[add-None]
tsa/tests/test_holtwinters.py::test_start_params[mul-add]
tsa/tests/test_holtwinters.py::test_start_params[mul-mul]
tsa/tests/test_holtwinters.py::test_start_params[mul-None]
tsa/tests/test_holtwinters.py::test_start_params[None-add]
tsa/tests/test_holtwinters.py::test_start_params[None-mul]
tsa/tests/test_holtwinters.py::test_start_params[None-None]
tsa/tests/test_holtwinters.py::test_basin_hopping
tsa/tests/test_holtwinters.py::test_debiased
tsa/tests/test_holtwinters.py::test_float_boxcox[add-add]
tsa/tests/test_holtwinters.py::test_float_boxcox[add-mul]
tsa/tests/test_holtwinters.py::test_float_boxcox[add-None]
tsa/tests/test_holtwinters.py::test_float_boxcox[mul-add]
tsa/tests/test_holtwinters.py::test_float_boxcox[mul-mul]
tsa/tests/test_holtwinters.py::test_float_boxcox[mul-None]
tsa/tests/test_holtwinters.py::test_float_boxcox[None-add]
tsa/tests/test_holtwinters.py::test_float_boxcox[None-mul]
tsa/tests/test_holtwinters.py::test_float_boxcox[None-None]
tsa/tests/test_holtwinters.py::test_direct_holt_add
tsa/tests/test_holtwinters.py::test_integer_array
tsa/tests/test_holtwinters.py::test_damping_slope_zero
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/holtwinters.py:731: RuntimeWarning: invalid value encountered in greater_equal
loc = initial_p >= ub
tsa/tests/test_holtwinters.py::TestHoltWinters::test_forecast
tsa/tests/test_holtwinters.py::TestHoltWinters::test_hw_seasonal_buggy
tsa/tests/test_holtwinters.py::test_float_boxcox[add-mul]
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/holtwinters.py:743: ConvergenceWarning: Optimization failed to converge. Check mle_retvals.
warn("Optimization failed to converge. Check mle_retvals.",
tsa/vector_ar/tests/test_var.py::TestVARResults::test_plot_irf
tsa/vector_ar/tests/test_var.py::TestVARResults::test_plot_irf
tsa/vector_ar/tests/test_var.py::TestVARResults::test_plot_irf
tsa/vector_ar/tests/test_var.py::TestVARResults::test_plot_irf
tsa/vector_ar/tests/test_var.py::TestVARResults::test_plot_irf
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.8_statsmodels/build/statsmodels/tsa/vector_ar/plotting.py:206: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
fig, axes = plt.subplots(nrows=nrows, ncols=ncols, sharex=True,
-- Docs: https://docs.pytest.org/en/latest/warnings.html
= 1 failed, 12159 passed, 172 skipped, 202 xfailed, 454 xpassed, 1361 warnings in 18393.22 seconds =
RUNNING THE L-BFGS-B CODE
* * *
Machine precision = 2.220D-16
N = 3 M = 12
This problem is unconstrained.
At X0 0 variables are exactly at the bounds
make[1]: *** [debian/rules:116: override_dh_auto_test] Error 1
make[1]: Leaving directory '/<<PKGBUILDDIR>>'
make: *** [debian/rules:23: binary-arch] Error 2
dpkg-buildpackage: error: debian/rules binary-arch subprocess returned exit status 2
--------------------------------------------------------------------------------
Build finished at 2020-04-28T13:31:38Z
Finished
--------
+------------------------------------------------------------------------------+
| Cleanup |
+------------------------------------------------------------------------------+
Purging /<<BUILDDIR>>
Not cleaning session: cloned chroot in use
E: Build failure (dpkg-buildpackage died)
+------------------------------------------------------------------------------+
| Summary |
+------------------------------------------------------------------------------+
Build Architecture: armhf
Build-Space: 0
Build-Time: 21416
Distribution: bullseye-staging
Fail-Stage: build
Host Architecture: armhf
Install-Time: 1254
Job: statsmodels_0.11.1-2
Machine Architecture: armhf
Package: statsmodels
Package-Time: 22725
Source-Version: 0.11.1-2
Space: 0
Status: failed
Version: 0.11.1-2
--------------------------------------------------------------------------------
Finished at 2020-04-28T13:31:38Z
Build needed 00:00:00, 0k disc space