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README.rst
1|PyPI Version| |Conda Version| |License| |Azure CI Build Status|
2|Codecov Coverage| |Coveralls Coverage| |PyPI downloads| |Conda downloads|
3
4About statsmodels
5=================
6
7statsmodels is a Python package that provides a complement to scipy for
8statistical computations including descriptive statistics and estimation
9and inference for statistical models.
10
11
12Documentation
13=============
14
15The documentation for the latest release is at
16
17https://www.statsmodels.org/stable/
18
19The documentation for the development version is at
20
21https://www.statsmodels.org/dev/
22
23Recent improvements are highlighted in the release notes
24
25https://www.statsmodels.org/stable/release/
26
27Backups of documentation are available at https://statsmodels.github.io/stable/
28and https://statsmodels.github.io/dev/.
29
30
31Main Features
32=============
33
34* Linear regression models:
35
36 - Ordinary least squares
37 - Generalized least squares
38 - Weighted least squares
39 - Least squares with autoregressive errors
40 - Quantile regression
41 - Recursive least squares
42
43* Mixed Linear Model with mixed effects and variance components
44* GLM: Generalized linear models with support for all of the one-parameter
45 exponential family distributions
46* Bayesian Mixed GLM for Binomial and Poisson
47* GEE: Generalized Estimating Equations for one-way clustered or longitudinal data
48* Discrete models:
49
50 - Logit and Probit
51 - Multinomial logit (MNLogit)
52 - Poisson and Generalized Poisson regression
53 - Negative Binomial regression
54 - Zero-Inflated Count models
55
56* RLM: Robust linear models with support for several M-estimators.
57* Time Series Analysis: models for time series analysis
58
59 - Complete StateSpace modeling framework
60
61 - Seasonal ARIMA and ARIMAX models
62 - VARMA and VARMAX models
63 - Dynamic Factor models
64 - Unobserved Component models
65
66 - Markov switching models (MSAR), also known as Hidden Markov Models (HMM)
67 - Univariate time series analysis: AR, ARIMA
68 - Vector autoregressive models, VAR and structural VAR
69 - Vector error correction model, VECM
70 - exponential smoothing, Holt-Winters
71 - Hypothesis tests for time series: unit root, cointegration and others
72 - Descriptive statistics and process models for time series analysis
73
74* Survival analysis:
75
76 - Proportional hazards regression (Cox models)
77 - Survivor function estimation (Kaplan-Meier)
78 - Cumulative incidence function estimation
79
80* Multivariate:
81
82 - Principal Component Analysis with missing data
83 - Factor Analysis with rotation
84 - MANOVA
85 - Canonical Correlation
86
87* Nonparametric statistics: Univariate and multivariate kernel density estimators
88* Datasets: Datasets used for examples and in testing
89* Statistics: a wide range of statistical tests
90
91 - diagnostics and specification tests
92 - goodness-of-fit and normality tests
93 - functions for multiple testing
94 - various additional statistical tests
95
96* Imputation with MICE, regression on order statistic and Gaussian imputation
97* Mediation analysis
98* Graphics includes plot functions for visual analysis of data and model results
99
100* I/O
101
102 - Tools for reading Stata .dta files, but pandas has a more recent version
103 - Table output to ascii, latex, and html
104
105* Miscellaneous models
106* Sandbox: statsmodels contains a sandbox folder with code in various stages of
107 development and testing which is not considered "production ready". This covers
108 among others
109
110 - Generalized method of moments (GMM) estimators
111 - Kernel regression
112 - Various extensions to scipy.stats.distributions
113 - Panel data models
114 - Information theoretic measures
115
116How to get it
117=============
118The main branch on GitHub is the most up to date code
119
120https://www.github.com/statsmodels/statsmodels
121
122Source download of release tags are available on GitHub
123
124https://github.com/statsmodels/statsmodels/tags
125
126Binaries and source distributions are available from PyPi
127
128https://pypi.org/project/statsmodels/
129
130Binaries can be installed in Anaconda
131
132conda install statsmodels
133
134
135Installing from sources
136=======================
137
138See INSTALL.txt for requirements or see the documentation
139
140https://statsmodels.github.io/dev/install.html
141
142Contributing
143============
144Contributions in any form are welcome, including:
145
146* Documentation improvements
147* Additional tests
148* New features to existing models
149* New models
150
151https://www.statsmodels.org/stable/dev/test_notes
152
153for instructions on installing statsmodels in *editable* mode.
154
155License
156=======
157
158Modified BSD (3-clause)
159
160Discussion and Development
161==========================
162
163Discussions take place on the mailing list
164
165https://groups.google.com/group/pystatsmodels
166
167and in the issue tracker. We are very interested in feedback
168about usability and suggestions for improvements.
169
170Bug Reports
171===========
172
173Bug reports can be submitted to the issue tracker at
174
175https://github.com/statsmodels/statsmodels/issues
176
177.. |Azure CI Build Status| image:: https://dev.azure.com/statsmodels/statsmodels-testing/_apis/build/status/statsmodels.statsmodels?branchName=main
178 :target: https://dev.azure.com/statsmodels/statsmodels-testing/_build/latest?definitionId=1&branchName=main
179.. |Codecov Coverage| image:: https://codecov.io/gh/statsmodels/statsmodels/branch/main/graph/badge.svg
180 :target: https://codecov.io/gh/statsmodels/statsmodels
181.. |Coveralls Coverage| image:: https://coveralls.io/repos/github/statsmodels/statsmodels/badge.svg?branch=main
182 :target: https://coveralls.io/github/statsmodels/statsmodels?branch=main
183.. |PyPI downloads| image:: https://img.shields.io/pypi/dm/statsmodels?label=PyPI%20Downloads
184 :alt: PyPI - Downloads
185 :target: https://pypi.org/project/statsmodels/
186.. |Conda downloads| image:: https://img.shields.io/conda/dn/conda-forge/statsmodels.svg?label=Conda%20downloads
187 :target: https://anaconda.org/conda-forge/statsmodels/
188.. |PyPI Version| image:: https://img.shields.io/pypi/v/statsmodels.svg
189 :target: https://pypi.org/project/statsmodels/
190.. |Conda Version| image:: https://anaconda.org/conda-forge/statsmodels/badges/version.svg
191 :target: https://anaconda.org/conda-forge/statsmodels/
192.. |License| image:: https://img.shields.io/pypi/l/statsmodels.svg
193 :target: https://github.com/statsmodels/statsmodels/blob/main/LICENSE.txt
194