Skip to main content

Statistical computations and models for use with SciPy

Project description

What it is

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: Generalized least squares (including weighted least squares and least squares with autoregressive errors), ordinary least squares.

  • 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 time series analysis: AR, ARIMA - vector autoregressive models, VAR and structural VAR - descriptive statistics and process models for time series analysis

  • 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 - goodness-of-fit and normality tests - functions for multiple testing - various additional statistical 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”. This covers among others Mixed (repeated measures) Models, GARCH models, general method of moments (GMM) estimators, kernel regression, various extensions to scipy.stats.distributions, panel data models, generalized additive models and information theoretic measures.

Where 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/

Installation from sources

See INSTALL.txt for requirements or see the documentation

http://statsmodels.sf.net/devel/install.html

License

Modified BSD (3-clause)

Documentation

The official documentation is hosted on SourceForge

http://statsmodels.sf.net/

Windows Help

We are providing a Windows htmlhelp file (statsmodels.chm) that is now separately distributed, available at http://sourceforge.net/projects/statsmodels/files/statsmodels-0.4.3/statsmodelsdoc.zip/download

It can be copied or moved to the installation directory of statsmodels (site-packagesstatsmodels in a typical installation), and can then be opened from the python interpreter

>>> import statsmodels.api as sm
>>> sm.open_help()

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

statsmodels-0.5.0rc1.zip (5.9 MB view details)

Uploaded Source

statsmodels-0.5.0rc1.tar.gz (5.5 MB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

statsmodels-0.5.0rc1.win-amd64-py3.2.exe (5.3 MB view details)

Uploaded Source

statsmodels-0.5.0rc1.win-amd64-py2.7.exe (5.3 MB view details)

Uploaded Source

statsmodels-0.5.0rc1.win-amd64-py2.6.exe (5.3 MB view details)

Uploaded Source

statsmodels-0.5.0rc1.win32-py3.2.exe (5.2 MB view details)

Uploaded Source

statsmodels-0.5.0rc1.win32-py2.7.exe (5.2 MB view details)

Uploaded Source

statsmodels-0.5.0rc1.win32-py2.6.exe (5.2 MB view details)

Uploaded Source

File details

Details for the file statsmodels-0.5.0rc1.zip.

File metadata

  • Download URL: statsmodels-0.5.0rc1.zip
  • Upload date:
  • Size: 5.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for statsmodels-0.5.0rc1.zip
Algorithm Hash digest
SHA256 e27548a1b8608dc603afa7324228f1ed9b1905a04412827963f39e4e6281933a
MD5 11266797eef0e7357656774b3d8a2c18
BLAKE2b-256 97cab32dd344cbbaa9edc11933aeffd752514186f47fcd87275b68e6022aab6d

See more details on using hashes here.

File details

Details for the file statsmodels-0.5.0rc1.tar.gz.

File metadata

File hashes

Hashes for statsmodels-0.5.0rc1.tar.gz
Algorithm Hash digest
SHA256 86b57fd760dcb2aa017c68cd143185002f9ac0ba54de63df02ed9812d58ef0d3
MD5 5fee56febb8f51da4c7212bb7f5e20a2
BLAKE2b-256 a688129a4bcc9cca683455c1541d723d7c3f5a5ac34e118f9128eb0769168b55

See more details on using hashes here.

File details

Details for the file statsmodels-0.5.0rc1.win-amd64-py3.2.exe.

File metadata

File hashes

Hashes for statsmodels-0.5.0rc1.win-amd64-py3.2.exe
Algorithm Hash digest
SHA256 0edb8a5a51d26722e552c221105720ee2be300053b10a3e74b25b98cab0e970c
MD5 7347d106434cb9bb2498372fcbe232ec
BLAKE2b-256 732ee458798468414177600975fdd933ed2900db0b68780e551fe4cd84584213

See more details on using hashes here.

File details

Details for the file statsmodels-0.5.0rc1.win-amd64-py2.7.exe.

File metadata

File hashes

Hashes for statsmodels-0.5.0rc1.win-amd64-py2.7.exe
Algorithm Hash digest
SHA256 990ecb2fac03458b54447b5cd0aba23c8af894a62a5b580c275cf192cdf2cdc0
MD5 e2aa81688108c608e9329e23bd8699be
BLAKE2b-256 a09cb60bd02bfdf6b0ad462f21dfadaad9cdcf757ef257c6c7c3e92346b2a4de

See more details on using hashes here.

File details

Details for the file statsmodels-0.5.0rc1.win-amd64-py2.6.exe.

File metadata

File hashes

Hashes for statsmodels-0.5.0rc1.win-amd64-py2.6.exe
Algorithm Hash digest
SHA256 619130d2dfdee61b2fe4223e7e488b4075e94aa4da3290eb75f18c4e24973c61
MD5 44532825493cf290bb420fbabfb64ee2
BLAKE2b-256 8f0d1d8bbc7d770307554f7a22873863707d9690a70c84a1c4d784a0b128c04a

See more details on using hashes here.

File details

Details for the file statsmodels-0.5.0rc1.win32-py3.2.exe.

File metadata

File hashes

Hashes for statsmodels-0.5.0rc1.win32-py3.2.exe
Algorithm Hash digest
SHA256 5325128e8eb9b29786a52dff64333b1c47b029ccb4e581b87c2cfa8ad4e043a6
MD5 84e538453419ff4271d736ce89512125
BLAKE2b-256 b160b04d0be0e68203acb1075dd1287132a2c044f3f2cfedef9b3689e2f8f3f4

See more details on using hashes here.

File details

Details for the file statsmodels-0.5.0rc1.win32-py2.7.exe.

File metadata

File hashes

Hashes for statsmodels-0.5.0rc1.win32-py2.7.exe
Algorithm Hash digest
SHA256 a07198222540ed733dbb0348a3b46abb7e53baeb2c21c01acb214123b4287a28
MD5 a0f8861b6e62f0797c6dd8abd0d7fcdd
BLAKE2b-256 a64ef2b0d8284b23a1ee9c21afb7ab65c9067888c50b84fac81be3f8e7d31e40

See more details on using hashes here.

File details

Details for the file statsmodels-0.5.0rc1.win32-py2.6.exe.

File metadata

File hashes

Hashes for statsmodels-0.5.0rc1.win32-py2.6.exe
Algorithm Hash digest
SHA256 9419b8dd2a3803b04db05b17e7252de9c3bea15263673b933ff6f1f84a6debfc
MD5 66e72b6413322f68e9d38ca23fedd8fd
BLAKE2b-256 02d48416da1351e0bac54ed2d23bcb3fbc0235151fa4ac05d244b0be492d8d49

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page