Welcome to statsmodels’s documentation!

scikits.statsmodels is a pure python package that provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families and M-estimators for robust linear models. An extensive list of result statistics are avalable for each estimation problem

Quickstart for the impatient

License: Simplified BSD

Requirements: python 2.4. to 2.6 and
recent releases of numpy (>=1.3) and scipy (>=0.7) earlier versions of numpy and scipy might work but not tested Optional: Many of the examples use matplotlib, and some sandbox functions have additional dependencies

Repository: http://code.launchpad.net/statsmodels

Documentation: http://statsmodels.sourceforge.net/
and in the docs/build folder

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

Mailing List: http://groups.google.com/group/pystatsmodels?hl=en

Bug Tracker: https://bugs.launchpad.net/statsmodels

Installation:

easy_install scikits.statsmodels

or get the source from pypi, sourceforge, or from the launchpad repository and

setup.py install  or, if this does not work, try
setup.py build install

Usage:

Get the data, run the estimation, and look at the results. For example, here is a minimal ordinary least squares case

import numpy as np
import scikits.statsmodels as sm

# get data
nsample = 100
x = np.linspace(0,10, 100)
X = sm.tools.add_constant(np.column_stack((x, x**2)))
beta = np.array([1, 0.1, 10])
y = np.dot(X, beta) + np.random.normal(size=nsample)

# run the regression
results = sm.OLS(y, X).fit()

# look at the results
print results.summary()

and look at `dir(results)` to see some of the results
that are available

Note: Due to our infrequent official releases, we want to point out that the trunk branch in the launchpad repository will have the most recent code and is usually stable and tested and fine for daily use.

Table of Contents

Indices and tables

Table Of Contents

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Introduction

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