git: ea0d963ab403 - main - math/py-statsmodels: Update WWW and pkg-descr

The branch main has been updated by sunpoet:

URL: https://cgit.FreeBSD.org/ports/commit/?id=ea0d963ab4038873ebb104fdea0a58c747fae06c

commit ea0d963ab4038873ebb104fdea0a58c747fae06c
Author:     Po-Chuan Hsieh <sunpoet@FreeBSD.org>
AuthorDate: 2024-05-16 06:18:23 +0000
Commit:     Po-Chuan Hsieh <sunpoet@FreeBSD.org>
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