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Thu, 16 May 2024 06:30:58 GMT (envelope-from git) Date: Thu, 16 May 2024 06:30:58 GMT Message-Id: <202405160630.44G6Uwh7044524@gitrepo.freebsd.org> To: ports-committers@FreeBSD.org, dev-commits-ports-all@FreeBSD.org, dev-commits-ports-main@FreeBSD.org From: Po-Chuan Hsieh Subject: git: ea0d963ab403 - main - math/py-statsmodels: Update WWW and pkg-descr List-Id: Commits to the main branch of the FreeBSD ports repository List-Archive: https://lists.freebsd.org/archives/dev-commits-ports-main List-Help: List-Post: List-Subscribe: List-Unsubscribe: X-BeenThere: dev-commits-ports-main@freebsd.org Sender: owner-dev-commits-ports-main@FreeBSD.org MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: 8bit X-Git-Committer: sunpoet X-Git-Repository: ports X-Git-Refname: refs/heads/main X-Git-Reftype: branch X-Git-Commit: ea0d963ab4038873ebb104fdea0a58c747fae06c Auto-Submitted: auto-generated The branch main has been updated by sunpoet: URL: https://cgit.FreeBSD.org/ports/commit/?id=ea0d963ab4038873ebb104fdea0a58c747fae06c commit ea0d963ab4038873ebb104fdea0a58c747fae06c Author: Po-Chuan Hsieh AuthorDate: 2024-05-16 06:18:23 +0000 Commit: Po-Chuan Hsieh CommitDate: 2024-05-16 06:22:08 +0000 math/py-statsmodels: Update WWW and pkg-descr --- math/py-statsmodels/Makefile | 3 ++- math/py-statsmodels/pkg-descr | 43 +++++++++++++++++++++++++------------------ 2 files changed, 27 insertions(+), 19 deletions(-) diff --git a/math/py-statsmodels/Makefile b/math/py-statsmodels/Makefile index 669980fc9f70..d6cbc65701a2 100644 --- a/math/py-statsmodels/Makefile +++ b/math/py-statsmodels/Makefile @@ -6,7 +6,8 @@ PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX} MAINTAINER= sunpoet@FreeBSD.org COMMENT= Complement to SciPy for statistical computations -WWW= https://github.com/statsmodels/statsmodels +WWW= https://www.statsmodels.org/stable/ \ + https://github.com/statsmodels/statsmodels LICENSE= BSD3CLAUSE LICENSE_FILE= ${WRKSRC}/LICENSE.txt diff --git a/math/py-statsmodels/pkg-descr b/math/py-statsmodels/pkg-descr index 5e5e83d80f62..a87433b76fc1 100644 --- a/math/py-statsmodels/pkg-descr +++ b/math/py-statsmodels/pkg-descr @@ -1,22 +1,29 @@ -Statsmodels is a Python package that provides a complement to scipy for +statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics and estimation and inference for statistical models. Main Features: -* linear regression models: GLS (including WLS and LS aith AR errors) and OLS. -* glm: Generalized linear models with support for all of the one-parameter - exponential family distributions. -* discrete: regression with discrete dependent variables, including Logit, - Probit, MNLogit, Poisson, based on maximum likelihood estimators -* rlm: Robust linear models with support for several M-estimators. -* tsa: models for time series analysis - univariate: AR, ARIMA; multivariate: - VAR and structural VAR -* nonparametric: (Univariate) kernel density estimators -* datasets: Datasets to be distributed and used for examples and in testing. -* stats: a wide range of statistical tests, diagnostics and specification tests -* iolib: Tools for reading Stata .dta files into numpy arrays, printing table - output to ascii, latex, and html -* miscellaneous models -* sandbox: statsmodels contains a sandbox folder with code in various stages of -* developement and testing which is not considered "production ready", including - Mixed models, GARCH and GMM estimators, kernel regression, panel data models. +- Linear regression models +- Mixed Linear Model with mixed effects and variance components +- GLM: Generalized linear models with support for all of the one-parameter + exponential family distributions +- Bayesian Mixed GLM for Binomial and Poisson +- GEE: Generalized Estimating Equations for one-way clustered or longitudinal + data +- Discrete models +- RLM: Robust linear models with support for several M-estimators. +- Time Series Analysis: models for time series analysis +- Survival analysis +- Multivariate +- Nonparametric statistics: Univariate and multivariate kernel density + estimators +- Datasets: Datasets used for examples and in testing +- Statistics: a wide range of statistical tests +- Imputation with MICE, regression on order statistic and Gaussian imputation +- Mediation analysis +- Graphics includes plot functions for visual analysis of data and model results +- I/O +- Miscellaneous models +- Sandbox: statsmodels contains a sandbox folder with code in various stages of + development and testing which is not considered "production ready". This + covers among others