Statistical computations and models for Python

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About Statsmodels

Statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics and estimation and inference for statistical models.

Documentation

The documentation for the latest release is at

http://www.statsmodels.org/stable/

The documentation for the development version is at

http://www.statsmodels.org/dev/

Recent improvements are highlighted in the release notes

http://www.statsmodels.org/stable/release/version0.8.html

Backups of documentation are available at http://statsmodels.github.io/stable/ and http://statsmodels.github.io/dev/.

Main Features

  • Linear regression models:

    • Ordinary least squares

    • Generalized least squares

    • Weighted least squares

    • Least squares with autoregressive errors

    • Quantile regression

  • Mixed Linear Model with mixed effects and variance components

  • GLM: Generalized linear models with support for all of the one-parameter exponential family distributions

  • GEE: Generalized Estimating Equations for one-way clustered or longitudinal data

  • Discrete models:

    • Logit and Probit

    • Multinomial logit (MNLogit)

    • Poisson regression

    • Negative Binomial regression

  • RLM: Robust linear models with support for several M-estimators.

  • Time Series Analysis: models for time series analysis

    • Complete StateSpace modeling framework

      • Seasonal ARIMA and ARIMAX models

      • VARMA and VARMAX models

      • Dynamic Factor models

    • Markov switching models (MSAR), also known as Hidden Markov Models (HMM)

    • Univariate time series analysis: AR, ARIMA

    • Vector autoregressive models, VAR and structural VAR

    • Hypothesis tests for time series: unit root, cointegration and others

    • Descriptive statistics and process models for time series analysis

  • Survival analysis:

    • Proportional hazards regression (Cox models)

    • Survivor function estimation (Kaplan-Meier)

    • Cumulative incidence function estimation

  • Nonparametric statistics: (Univariate) kernel density estimators

  • Datasets: Datasets used for examples and in testing

  • Statistics: a wide range of statistical tests

    • diagnostics and specification tests

    • goodness-of-fit and normality tests

    • functions for multiple testing

    • various additional statistical tests

  • Imputation with MICE and regression on order statistic

  • Mediation analysis

  • Principal Component Analysis with missing data

  • I/O

    • Tools for reading Stata .dta files into numpy arrays.

    • Table output to ASCII, LaTeX, and HTML

  • 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

    • Generalized method of moments (GMM) estimators

    • Kernel regression

    • Various extensions to scipy.stats.distributions

    • Panel data models

    • Information theoretic measures

How to get it

The master branch on GitHub is the most up to date code

https://www.github.com/statsmodels/statsmodels

Source download of release tags are available on GitHub

https://github.com/statsmodels/statsmodels/tags

Binaries and source distributions are available from PyPi

http://pypi.python.org/pypi/statsmodels/

Binaries can be installed in Anaconda

conda install statsmodels

Development snapshots are also available in Anaconda (infrequently updated)

conda install -c https://conda.binstar.org/statsmodels statsmodels

Installing from sources

See INSTALL.txt for requirements or see the documentation

http://statsmodels.github.io/dev/install.html

License

Modified BSD (3-clause)

Discussion and Development

Discussions take place on our mailing list.

http://groups.google.com/group/pystatsmodels

We are very interested in feedback about usability and suggestions for improvements.

Bug Reports

Bug reports can be submitted to the issue tracker at

https://github.com/statsmodels/statsmodels/issues

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0.14.4

0.14.3

0.14.2

0.14.1

0.14.0

0.14.0rc0 pre-release

0.13.5

0.13.4

0.13.3

0.13.2

0.13.1

0.13.0

0.13.0rc0 pre-release

0.12.2

0.12.1

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0.12.0rc0 pre-release

0.11.1

0.11.0

0.11.0rc2 pre-release

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0.10.2

0.10.1

0.10.0

0.10.0rc2 pre-release

0.9.0

0.9.0rc1 pre-release

This version

0.8.0

0.8.0rc1 pre-release

0.6.1

0.6.0

0.6.0-rc2 pre-release

0.6.0-rc1 pre-release

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