Received: by mail.netbsd.org (Postfix, from userid 605) id E952184E77; Mon, 8 May 2023 08:51:05 +0000 (UTC) Received: from localhost (localhost [127.0.0.1]) by mail.netbsd.org (Postfix) with ESMTP id 2262484D9B for ; Mon, 8 May 2023 08:51:05 +0000 (UTC) X-Virus-Scanned: amavisd-new at netbsd.org Received: from mail.netbsd.org ([IPv6:::1]) by localhost (mail.netbsd.org [IPv6:::1]) (amavisd-new, port 10025) with ESMTP id 8lqejxLZjUfa for ; Mon, 8 May 2023 08:51:03 +0000 (UTC) Received: from cvs.NetBSD.org (ivanova.netbsd.org [199.233.217.197]) by mail.netbsd.org (Postfix) with ESMTP id 6453184CF7 for ; Mon, 8 May 2023 08:51:03 +0000 (UTC) Received: by cvs.NetBSD.org (Postfix, from userid 500) id 5DE4AFA87; Mon, 8 May 2023 08:51:03 +0000 (UTC) Content-Transfer-Encoding: 7bit Content-Type: multipart/mixed; boundary="_----------=_168353586391060" MIME-Version: 1.0 Date: Mon, 8 May 2023 08:51:03 +0000 From: "Adam Ciarcinski" Subject: CVS commit: pkgsrc/math/py-statsmodels To: pkgsrc-changes@NetBSD.org Reply-To: adam@netbsd.org X-Mailer: log_accum Message-Id: <20230508085103.5DE4AFA87@cvs.NetBSD.org> Sender: pkgsrc-changes-owner@NetBSD.org List-Id: Precedence: bulk List-Unsubscribe: This is a multi-part message in MIME format. --_----------=_168353586391060 Content-Disposition: inline Content-Transfer-Encoding: 8bit Content-Type: text/plain; charset="US-ASCII" Module Name: pkgsrc Committed By: adam Date: Mon May 8 08:51:03 UTC 2023 Modified Files: pkgsrc/math/py-statsmodels: Makefile PLIST distinfo Log Message: py-statsmodels: updated to 0.14.0 Release 0.14.0 The Highlights ============== New cross-sectional models and extensions to models --------------------------------------------------- Treatment Effect ~~~~~~~~~~~~~~~~ :class:`~statsmodels.treatment.TreatmentEffect` estimates treatment effect for a binary treatment and potential outcome for a continuous outcome variable using 5 different methods, ipw, ra, aipw, aipw-wls, ipw-ra. Standard errors and inference are based on the joint GMM representation of selection or treatment model, outcome model and effect functions. Hurdle and Truncated Count Regression ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :class:`statsmodels.discrete.truncated_model.HurdleCountModel` implements hurdle models for count data with either Poisson or NegativeBinomialP as submodels. Three left truncated models used for zero truncation are available, :class:`statsmodels.discrete.truncated_model.TruncatedLFPoisson`, :class:`statsmodels.discrete.truncated_model.TruncatedLFNegativeBinomialP` and :class:`statsmodels.discrete.truncated_model.TruncatedLFGeneralizedPoisson`. Models for right censoring at one are implemented but only as support for the hurdle models. Extended postestimation methods for models ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Results methods for post-estimation have been added or extended. ``get_distribution`` returns a scipy or scipy compatible distribution instance with parameters based on the estimated model. This is available for GLM, discrete models and BetaModel. ``get_prediction`` returns predicted statistics including inferential statistics, standard errors and confidence intervals. The ``which`` keyword selects which statistic is predicted. Inference for statistics that are nonlinear in the estimated parameters are based on the delta-method for standard errors. ``get_diagnostic`` returns a Diagnostic class with additional specification statistics, tests and plots. Currently only available for count models. ``get_influence`` returns a class with outlier and influence diagnostics. (This was mostly added in previous releases.) ``score_test`` makes score (LM) test available as alternative to Wald tests. This is currently available for GLM and some discrete models. The score tests can optionally be robust to misspecification similar to ``cov_type`` for wald tests. Stats ~~~~~ Hypothesis tests, confidence intervals and other inferential statistics are now available for one and two sample Poisson rates. Distributions ~~~~~~~~~~~~~ Methods of Archimedean copulas have been extended to multivariate copulas with dimension larger than 2. The ``pdf`` method of Frank and Gumbel has been extended only to dimensions 3 and 4. New class ECDFDiscrete for empirical distribution function when observations are not unique as in discrete distributions. Multiseason STL decomposition (MSTL) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The existing :class:`~statsmodels.tsa.seasonal.STL` class has been extended to handle multiple seasonal components in :class:`~statsmodels.tsa.seasonal.MSTL`. To generate a diff of this commit: cvs rdiff -u -r1.14 -r1.15 pkgsrc/math/py-statsmodels/Makefile cvs rdiff -u -r1.8 -r1.9 pkgsrc/math/py-statsmodels/PLIST cvs rdiff -u -r1.9 -r1.10 pkgsrc/math/py-statsmodels/distinfo Please note that diffs are not public domain; they are subject to the copyright notices on the relevant files. --_----------=_168353586391060 Content-Disposition: inline Content-Length: 17961 Content-Transfer-Encoding: binary Content-Type: text/x-diff; charset=us-ascii Modified files: Index: pkgsrc/math/py-statsmodels/Makefile diff -u pkgsrc/math/py-statsmodels/Makefile:1.14 pkgsrc/math/py-statsmodels/Makefile:1.15 --- pkgsrc/math/py-statsmodels/Makefile:1.14 Wed Nov 23 23:48:02 2022 +++ pkgsrc/math/py-statsmodels/Makefile Mon May 8 08:51:03 2023 @@ -1,6 +1,6 @@ -# $NetBSD: Makefile,v 1.14 2022/11/23 23:48:02 wiz Exp $ +# $NetBSD: Makefile,v 1.15 2023/05/08 08:51:03 adam Exp $ -DISTNAME= statsmodels-0.13.5 +DISTNAME= statsmodels-0.14.0 PKGNAME= ${PYPKGPREFIX}-${DISTNAME} CATEGORIES= math python MASTER_SITES= ${MASTER_SITE_PYPI:=s/statsmodels/} @@ -10,20 +10,23 @@ HOMEPAGE= https://www.statsmodels.org/ COMMENT= Statistical computations and models for Python LICENSE= modified-bsd -PYTHON_VERSIONS_INCOMPATIBLE= 27 37 # py-scipy -USE_LANGUAGES= c - -TOOL_DEPENDS+= ${PYPKGPREFIX}-cython>=0.29:../../devel/py-cython -TOOL_DEPENDS+= ${PYPKGPREFIX}-setuptools_scm-[0-9]*:../../devel/py-setuptools_scm +TOOL_DEPENDS+= ${PYPKGPREFIX}-cython>=0.29.28:../../devel/py-cython +TOOL_DEPENDS+= ${PYPKGPREFIX}-setuptools_scm>=7.0.0:../../devel/py-setuptools_scm +DEPENDS+= ${PYPKGPREFIX}-packaging>=21.3:../../devel/py-packaging DEPENDS+= ${PYPKGPREFIX}-pandas>=0.21:../../math/py-pandas -DEPENDS+= ${PYPKGPREFIX}-patsy>=0.5:../../math/py-patsy -DEPENDS+= ${PYPKGPREFIX}-scipy>=1.1:../../math/py-scipy +DEPENDS+= ${PYPKGPREFIX}-patsy>=0.5.2:../../math/py-patsy +DEPENDS+= ${PYPKGPREFIX}-scipy>=1.9.3:../../math/py-scipy +TEST_DEPENDS+= ${PYPKGPREFIX}-test>=7.0.1:../../devel/py-test +TEST_DEPENDS+= ${PYPKGPREFIX}-test-randomly-[0-9]*:../../devel/py-test-randomly +TEST_DEPENDS+= ${PYPKGPREFIX}-test-xdist-[0-9]*:../../devel/py-test-xdist + +PYTHON_VERSIONS_INCOMPATIBLE= 27 37 # py-scipy -post-extract: - ${CHMOD} -R o-w,g-w ${WRKSRC} - ${FIND} ${WRKSRC} -type f -printx | ${XARGS} ${CHMOD} a-x +# FIXME: conflicts with installed tests +do-test: + cd ${WRKSRC} && ${SETENV} ${TEST_ENV} pytest-${PYVERSSUFFIX} statsmodels .include "../../lang/python/egg.mk" -BUILDLINK_API_DEPENDS.py-numpy+= ${PYPKGPREFIX}-numpy>=1.15 +BUILDLINK_API_DEPENDS.py-numpy+= ${PYPKGPREFIX}-numpy>=1.18 .include "../../math/py-numpy/buildlink3.mk" .include "../../mk/bsd.pkg.mk" Index: pkgsrc/math/py-statsmodels/PLIST diff -u pkgsrc/math/py-statsmodels/PLIST:1.8 pkgsrc/math/py-statsmodels/PLIST:1.9 --- pkgsrc/math/py-statsmodels/PLIST:1.8 Mon Nov 21 09:40:59 2022 +++ pkgsrc/math/py-statsmodels/PLIST Mon May 8 08:51:03 2023 @@ -1,4 +1,4 @@ -@comment $NetBSD: PLIST,v 1.8 2022/11/21 09:40:59 wiz Exp $ +@comment $NetBSD: PLIST,v 1.9 2023/05/08 08:51:03 adam Exp $ ${PYSITELIB}/${EGG_INFODIR}/PKG-INFO ${PYSITELIB}/${EGG_INFODIR}/SOURCES.txt ${PYSITELIB}/${EGG_INFODIR}/dependency_links.txt @@ -30,6 +30,9 @@ ${PYSITELIB}/statsmodels/base/_penalized ${PYSITELIB}/statsmodels/base/_penalties.py ${PYSITELIB}/statsmodels/base/_penalties.pyc ${PYSITELIB}/statsmodels/base/_penalties.pyo +${PYSITELIB}/statsmodels/base/_prediction_inference.py +${PYSITELIB}/statsmodels/base/_prediction_inference.pyc +${PYSITELIB}/statsmodels/base/_prediction_inference.pyo ${PYSITELIB}/statsmodels/base/_screening.py ${PYSITELIB}/statsmodels/base/_screening.pyc ${PYSITELIB}/statsmodels/base/_screening.pyo @@ -111,6 +114,9 @@ ${PYSITELIB}/statsmodels/compat/numpy.py ${PYSITELIB}/statsmodels/compat/pandas.py ${PYSITELIB}/statsmodels/compat/pandas.pyc ${PYSITELIB}/statsmodels/compat/pandas.pyo +${PYSITELIB}/statsmodels/compat/patsy.py +${PYSITELIB}/statsmodels/compat/patsy.pyc +${PYSITELIB}/statsmodels/compat/patsy.pyo ${PYSITELIB}/statsmodels/compat/platform.py ${PYSITELIB}/statsmodels/compat/platform.pyc ${PYSITELIB}/statsmodels/compat/platform.pyo @@ -374,6 +380,9 @@ ${PYSITELIB}/statsmodels/discrete/condit ${PYSITELIB}/statsmodels/discrete/count_model.py ${PYSITELIB}/statsmodels/discrete/count_model.pyc ${PYSITELIB}/statsmodels/discrete/count_model.pyo +${PYSITELIB}/statsmodels/discrete/diagnostic.py +${PYSITELIB}/statsmodels/discrete/diagnostic.pyc +${PYSITELIB}/statsmodels/discrete/diagnostic.pyo ${PYSITELIB}/statsmodels/discrete/discrete_margins.py ${PYSITELIB}/statsmodels/discrete/discrete_margins.pyc ${PYSITELIB}/statsmodels/discrete/discrete_margins.pyo @@ -407,6 +416,15 @@ ${PYSITELIB}/statsmodels/discrete/tests/ ${PYSITELIB}/statsmodels/discrete/tests/results/results_poisson_constrained.py ${PYSITELIB}/statsmodels/discrete/tests/results/results_poisson_constrained.pyc ${PYSITELIB}/statsmodels/discrete/tests/results/results_poisson_constrained.pyo +${PYSITELIB}/statsmodels/discrete/tests/results/results_predict.py +${PYSITELIB}/statsmodels/discrete/tests/results/results_predict.pyc +${PYSITELIB}/statsmodels/discrete/tests/results/results_predict.pyo +${PYSITELIB}/statsmodels/discrete/tests/results/results_truncated.py +${PYSITELIB}/statsmodels/discrete/tests/results/results_truncated.pyc +${PYSITELIB}/statsmodels/discrete/tests/results/results_truncated.pyo +${PYSITELIB}/statsmodels/discrete/tests/results/results_truncated_st.py +${PYSITELIB}/statsmodels/discrete/tests/results/results_truncated_st.pyc +${PYSITELIB}/statsmodels/discrete/tests/results/results_truncated_st.pyo ${PYSITELIB}/statsmodels/discrete/tests/results/ships.csv ${PYSITELIB}/statsmodels/discrete/tests/results/sm3533.csv ${PYSITELIB}/statsmodels/discrete/tests/results/yhat_mnlogit.csv @@ -429,9 +447,18 @@ ${PYSITELIB}/statsmodels/discrete/tests/ ${PYSITELIB}/statsmodels/discrete/tests/test_margins.py ${PYSITELIB}/statsmodels/discrete/tests/test_margins.pyc ${PYSITELIB}/statsmodels/discrete/tests/test_margins.pyo +${PYSITELIB}/statsmodels/discrete/tests/test_predict.py +${PYSITELIB}/statsmodels/discrete/tests/test_predict.pyc +${PYSITELIB}/statsmodels/discrete/tests/test_predict.pyo ${PYSITELIB}/statsmodels/discrete/tests/test_sandwich_cov.py ${PYSITELIB}/statsmodels/discrete/tests/test_sandwich_cov.pyc ${PYSITELIB}/statsmodels/discrete/tests/test_sandwich_cov.pyo +${PYSITELIB}/statsmodels/discrete/tests/test_truncated_model.py +${PYSITELIB}/statsmodels/discrete/tests/test_truncated_model.pyc +${PYSITELIB}/statsmodels/discrete/tests/test_truncated_model.pyo +${PYSITELIB}/statsmodels/discrete/truncated_model.py +${PYSITELIB}/statsmodels/discrete/truncated_model.pyc +${PYSITELIB}/statsmodels/discrete/truncated_model.pyo ${PYSITELIB}/statsmodels/distributions/__init__.py ${PYSITELIB}/statsmodels/distributions/__init__.pyc ${PYSITELIB}/statsmodels/distributions/__init__.pyo @@ -441,6 +468,9 @@ ${PYSITELIB}/statsmodels/distributions/b ${PYSITELIB}/statsmodels/distributions/copula/__init__.py ${PYSITELIB}/statsmodels/distributions/copula/__init__.pyc ${PYSITELIB}/statsmodels/distributions/copula/__init__.pyo +${PYSITELIB}/statsmodels/distributions/copula/_special.py +${PYSITELIB}/statsmodels/distributions/copula/_special.pyc +${PYSITELIB}/statsmodels/distributions/copula/_special.pyo ${PYSITELIB}/statsmodels/distributions/copula/api.py ${PYSITELIB}/statsmodels/distributions/copula/api.pyc ${PYSITELIB}/statsmodels/distributions/copula/api.pyo @@ -663,9 +693,6 @@ ${PYSITELIB}/statsmodels/gam/tests/test_ ${PYSITELIB}/statsmodels/genmod/__init__.py ${PYSITELIB}/statsmodels/genmod/__init__.pyc ${PYSITELIB}/statsmodels/genmod/__init__.pyo -${PYSITELIB}/statsmodels/genmod/_prediction.py -${PYSITELIB}/statsmodels/genmod/_prediction.pyc -${PYSITELIB}/statsmodels/genmod/_prediction.pyo ${PYSITELIB}/statsmodels/genmod/_tweedie_compound_poisson.py ${PYSITELIB}/statsmodels/genmod/_tweedie_compound_poisson.pyc ${PYSITELIB}/statsmodels/genmod/_tweedie_compound_poisson.pyo @@ -995,9 +1022,6 @@ ${PYSITELIB}/statsmodels/miscmodels/test ${PYSITELIB}/statsmodels/miscmodels/tests/test_poisson.py ${PYSITELIB}/statsmodels/miscmodels/tests/test_poisson.pyc ${PYSITELIB}/statsmodels/miscmodels/tests/test_poisson.pyo -${PYSITELIB}/statsmodels/miscmodels/tests/test_tarma.py -${PYSITELIB}/statsmodels/miscmodels/tests/test_tarma.pyc -${PYSITELIB}/statsmodels/miscmodels/tests/test_tarma.pyo ${PYSITELIB}/statsmodels/miscmodels/tests/test_tmodel.py ${PYSITELIB}/statsmodels/miscmodels/tests/test_tmodel.pyc ${PYSITELIB}/statsmodels/miscmodels/tests/test_tmodel.pyo @@ -1326,9 +1350,18 @@ ${PYSITELIB}/statsmodels/robust/tests/__ ${PYSITELIB}/statsmodels/robust/tests/results/__init__.py ${PYSITELIB}/statsmodels/robust/tests/results/__init__.pyc ${PYSITELIB}/statsmodels/robust/tests/results/__init__.pyo +${PYSITELIB}/statsmodels/robust/tests/results/results_norms.py +${PYSITELIB}/statsmodels/robust/tests/results/results_norms.pyc +${PYSITELIB}/statsmodels/robust/tests/results/results_norms.pyo ${PYSITELIB}/statsmodels/robust/tests/results/results_rlm.py ${PYSITELIB}/statsmodels/robust/tests/results/results_rlm.pyc ${PYSITELIB}/statsmodels/robust/tests/results/results_rlm.pyo +${PYSITELIB}/statsmodels/robust/tests/test_mquantiles.py +${PYSITELIB}/statsmodels/robust/tests/test_mquantiles.pyc +${PYSITELIB}/statsmodels/robust/tests/test_mquantiles.pyo +${PYSITELIB}/statsmodels/robust/tests/test_norms.py +${PYSITELIB}/statsmodels/robust/tests/test_norms.pyc +${PYSITELIB}/statsmodels/robust/tests/test_norms.pyo ${PYSITELIB}/statsmodels/robust/tests/test_rlm.py ${PYSITELIB}/statsmodels/robust/tests/test_rlm.pyc ${PYSITELIB}/statsmodels/robust/tests/test_rlm.pyo @@ -1737,9 +1770,15 @@ ${PYSITELIB}/statsmodels/stats/__init__. ${PYSITELIB}/statsmodels/stats/_adnorm.py ${PYSITELIB}/statsmodels/stats/_adnorm.pyc ${PYSITELIB}/statsmodels/stats/_adnorm.pyo +${PYSITELIB}/statsmodels/stats/_delta_method.py +${PYSITELIB}/statsmodels/stats/_delta_method.pyc +${PYSITELIB}/statsmodels/stats/_delta_method.pyo ${PYSITELIB}/statsmodels/stats/_diagnostic_other.py ${PYSITELIB}/statsmodels/stats/_diagnostic_other.pyc ${PYSITELIB}/statsmodels/stats/_diagnostic_other.pyo +${PYSITELIB}/statsmodels/stats/_inference_tools.py +${PYSITELIB}/statsmodels/stats/_inference_tools.pyc +${PYSITELIB}/statsmodels/stats/_inference_tools.pyo ${PYSITELIB}/statsmodels/stats/_knockoff.py ${PYSITELIB}/statsmodels/stats/_knockoff.pyc ${PYSITELIB}/statsmodels/stats/_knockoff.pyo @@ -1928,6 +1967,9 @@ ${PYSITELIB}/statsmodels/stats/tests/tes ${PYSITELIB}/statsmodels/stats/tests/test_corrpsd.pyc ${PYSITELIB}/statsmodels/stats/tests/test_corrpsd.pyo ${PYSITELIB}/statsmodels/stats/tests/test_data.txt +${PYSITELIB}/statsmodels/stats/tests/test_deltacov.py +${PYSITELIB}/statsmodels/stats/tests/test_deltacov.pyc +${PYSITELIB}/statsmodels/stats/tests/test_deltacov.pyo ${PYSITELIB}/statsmodels/stats/tests/test_descriptivestats.py ${PYSITELIB}/statsmodels/stats/tests/test_descriptivestats.pyc ${PYSITELIB}/statsmodels/stats/tests/test_descriptivestats.pyo @@ -2036,6 +2078,9 @@ ${PYSITELIB}/statsmodels/tests/__init__. ${PYSITELIB}/statsmodels/tests/test_package.py ${PYSITELIB}/statsmodels/tests/test_package.pyc ${PYSITELIB}/statsmodels/tests/test_package.pyo +${PYSITELIB}/statsmodels/tests/test_x13.py +${PYSITELIB}/statsmodels/tests/test_x13.pyc +${PYSITELIB}/statsmodels/tests/test_x13.pyo ${PYSITELIB}/statsmodels/tools/__init__.py ${PYSITELIB}/statsmodels/tools/__init__.pyc ${PYSITELIB}/statsmodels/tools/__init__.pyo @@ -2141,6 +2186,9 @@ ${PYSITELIB}/statsmodels/tools/tools.pyo ${PYSITELIB}/statsmodels/tools/transform_model.py ${PYSITELIB}/statsmodels/tools/transform_model.pyc ${PYSITELIB}/statsmodels/tools/transform_model.pyo +${PYSITELIB}/statsmodels/tools/typing.py +${PYSITELIB}/statsmodels/tools/typing.pyc +${PYSITELIB}/statsmodels/tools/typing.pyo ${PYSITELIB}/statsmodels/tools/validation/__init__.py ${PYSITELIB}/statsmodels/tools/validation/__init__.pyc ${PYSITELIB}/statsmodels/tools/validation/__init__.pyo @@ -2159,6 +2207,25 @@ ${PYSITELIB}/statsmodels/tools/validatio ${PYSITELIB}/statsmodels/tools/web.py ${PYSITELIB}/statsmodels/tools/web.pyc ${PYSITELIB}/statsmodels/tools/web.pyo +${PYSITELIB}/statsmodels/treatment/__init__.py +${PYSITELIB}/statsmodels/treatment/__init__.pyc +${PYSITELIB}/statsmodels/treatment/__init__.pyo +${PYSITELIB}/statsmodels/treatment/tests/__init__.py +${PYSITELIB}/statsmodels/treatment/tests/__init__.pyc +${PYSITELIB}/statsmodels/treatment/tests/__init__.pyo +${PYSITELIB}/statsmodels/treatment/tests/results/__init__.py +${PYSITELIB}/statsmodels/treatment/tests/results/__init__.pyc +${PYSITELIB}/statsmodels/treatment/tests/results/__init__.pyo +${PYSITELIB}/statsmodels/treatment/tests/results/cataneo2.csv +${PYSITELIB}/statsmodels/treatment/tests/results/results_teffects.py +${PYSITELIB}/statsmodels/treatment/tests/results/results_teffects.pyc +${PYSITELIB}/statsmodels/treatment/tests/results/results_teffects.pyo +${PYSITELIB}/statsmodels/treatment/tests/test_teffects.py +${PYSITELIB}/statsmodels/treatment/tests/test_teffects.pyc +${PYSITELIB}/statsmodels/treatment/tests/test_teffects.pyo +${PYSITELIB}/statsmodels/treatment/treatment_effects.py +${PYSITELIB}/statsmodels/treatment/treatment_effects.pyc +${PYSITELIB}/statsmodels/treatment/treatment_effects.pyo ${PYSITELIB}/statsmodels/tsa/__init__.py ${PYSITELIB}/statsmodels/tsa/__init__.pyc ${PYSITELIB}/statsmodels/tsa/__init__.pyo @@ -2166,7 +2233,6 @@ ${PYSITELIB}/statsmodels/tsa/_bds.py ${PYSITELIB}/statsmodels/tsa/_bds.pyc ${PYSITELIB}/statsmodels/tsa/_bds.pyo ${PYSITELIB}/statsmodels/tsa/_innovations.so -${PYSITELIB}/statsmodels/tsa/_stl.so ${PYSITELIB}/statsmodels/tsa/adfvalues.py ${PYSITELIB}/statsmodels/tsa/adfvalues.pyc ${PYSITELIB}/statsmodels/tsa/adfvalues.pyo @@ -2704,6 +2770,9 @@ ${PYSITELIB}/statsmodels/tsa/statespace/ ${PYSITELIB}/statsmodels/tsa/statespace/tests/test_conserve_memory.py ${PYSITELIB}/statsmodels/tsa/statespace/tests/test_conserve_memory.pyc ${PYSITELIB}/statsmodels/tsa/statespace/tests/test_conserve_memory.pyo +${PYSITELIB}/statsmodels/tsa/statespace/tests/test_decompose.py +${PYSITELIB}/statsmodels/tsa/statespace/tests/test_decompose.pyc +${PYSITELIB}/statsmodels/tsa/statespace/tests/test_decompose.pyo ${PYSITELIB}/statsmodels/tsa/statespace/tests/test_dynamic_factor.py ${PYSITELIB}/statsmodels/tsa/statespace/tests/test_dynamic_factor.pyc ${PYSITELIB}/statsmodels/tsa/statespace/tests/test_dynamic_factor.pyo @@ -2791,6 +2860,9 @@ ${PYSITELIB}/statsmodels/tsa/statespace/ ${PYSITELIB}/statsmodels/tsa/statespace/tests/test_varmax.py ${PYSITELIB}/statsmodels/tsa/statespace/tests/test_varmax.pyc ${PYSITELIB}/statsmodels/tsa/statespace/tests/test_varmax.pyo +${PYSITELIB}/statsmodels/tsa/statespace/tests/test_weights.py +${PYSITELIB}/statsmodels/tsa/statespace/tests/test_weights.pyc +${PYSITELIB}/statsmodels/tsa/statespace/tests/test_weights.pyo ${PYSITELIB}/statsmodels/tsa/statespace/tools.py ${PYSITELIB}/statsmodels/tsa/statespace/tools.pyc ${PYSITELIB}/statsmodels/tsa/statespace/tools.pyo @@ -2800,6 +2872,22 @@ ${PYSITELIB}/statsmodels/tsa/statespace/ ${PYSITELIB}/statsmodels/tsa/stattools.py ${PYSITELIB}/statsmodels/tsa/stattools.pyc ${PYSITELIB}/statsmodels/tsa/stattools.pyo +${PYSITELIB}/statsmodels/tsa/stl/__init__.py +${PYSITELIB}/statsmodels/tsa/stl/__init__.pyc +${PYSITELIB}/statsmodels/tsa/stl/__init__.pyo +${PYSITELIB}/statsmodels/tsa/stl/_stl.so +${PYSITELIB}/statsmodels/tsa/stl/mstl.py +${PYSITELIB}/statsmodels/tsa/stl/mstl.pyc +${PYSITELIB}/statsmodels/tsa/stl/mstl.pyo +${PYSITELIB}/statsmodels/tsa/stl/tests/__init__.py +${PYSITELIB}/statsmodels/tsa/stl/tests/__init__.pyc +${PYSITELIB}/statsmodels/tsa/stl/tests/__init__.pyo +${PYSITELIB}/statsmodels/tsa/stl/tests/test_mstl.py +${PYSITELIB}/statsmodels/tsa/stl/tests/test_mstl.pyc +${PYSITELIB}/statsmodels/tsa/stl/tests/test_mstl.pyo +${PYSITELIB}/statsmodels/tsa/stl/tests/test_stl.py +${PYSITELIB}/statsmodels/tsa/stl/tests/test_stl.pyc +${PYSITELIB}/statsmodels/tsa/stl/tests/test_stl.pyo ${PYSITELIB}/statsmodels/tsa/tests/__init__.py ${PYSITELIB}/statsmodels/tsa/tests/__init__.pyc ${PYSITELIB}/statsmodels/tsa/tests/__init__.pyo @@ -2896,8 +2984,6 @@ ${PYSITELIB}/statsmodels/tsa/tests/resul ${PYSITELIB}/statsmodels/tsa/tests/results/savedrvs.pyc ${PYSITELIB}/statsmodels/tsa/tests/results/savedrvs.pyo ${PYSITELIB}/statsmodels/tsa/tests/results/stkprc.csv -${PYSITELIB}/statsmodels/tsa/tests/results/stl_co2.csv -${PYSITELIB}/statsmodels/tsa/tests/results/stl_test_results.csv ${PYSITELIB}/statsmodels/tsa/tests/results/y_arma_data.csv ${PYSITELIB}/statsmodels/tsa/tests/results/yhat_css_c.csv ${PYSITELIB}/statsmodels/tsa/tests/results/yhat_css_nc.csv @@ -2927,9 +3013,6 @@ ${PYSITELIB}/statsmodels/tsa/tests/test_ ${PYSITELIB}/statsmodels/tsa/tests/test_stattools.py ${PYSITELIB}/statsmodels/tsa/tests/test_stattools.pyc ${PYSITELIB}/statsmodels/tsa/tests/test_stattools.pyo -${PYSITELIB}/statsmodels/tsa/tests/test_stl.py -${PYSITELIB}/statsmodels/tsa/tests/test_stl.pyc -${PYSITELIB}/statsmodels/tsa/tests/test_stl.pyo ${PYSITELIB}/statsmodels/tsa/tests/test_tsa_tools.py ${PYSITELIB}/statsmodels/tsa/tests/test_tsa_tools.pyc ${PYSITELIB}/statsmodels/tsa/tests/test_tsa_tools.pyo Index: pkgsrc/math/py-statsmodels/distinfo diff -u pkgsrc/math/py-statsmodels/distinfo:1.9 pkgsrc/math/py-statsmodels/distinfo:1.10 --- pkgsrc/math/py-statsmodels/distinfo:1.9 Mon Nov 21 09:40:59 2022 +++ pkgsrc/math/py-statsmodels/distinfo Mon May 8 08:51:03 2023 @@ -1,5 +1,5 @@ -$NetBSD: distinfo,v 1.9 2022/11/21 09:40:59 wiz Exp $ +$NetBSD: distinfo,v 1.10 2023/05/08 08:51:03 adam Exp $ -BLAKE2s (statsmodels-0.13.5.tar.gz) = 9d8c02dc5b0a78d3ffea3fdf119cac96e13b469f39e42598aaa8775d415fa9a5 -SHA512 (statsmodels-0.13.5.tar.gz) = 9aeeea80c69f52459140179523a0155429834b2951325c9781b28f8c4cbbd0593ff1867e2212078f2b898e4da953689c2fe78183d3c7959caa874e9d758b4ea4 -Size (statsmodels-0.13.5.tar.gz) = 18364957 bytes +BLAKE2s (statsmodels-0.14.0.tar.gz) = 568fe2bf6f24d4c10d48571586766f895f6584ec3b35926cccf15b5c032e49ba +SHA512 (statsmodels-0.14.0.tar.gz) = 876cc45eb4b5badee2ff859df8a45ce7c4f6ab2973d481f58c5b7906ebcdbb56a64769d5dd7a38c7b7415a4ee7cf98cf300b8c623bda9df001b982ff6844d1fd +Size (statsmodels-0.14.0.tar.gz) = 19374614 bytes --_----------=_168353586391060--