Getting started This very simple case-study is designed to get you up-and-running quickly with statsmodels. Starting from raw data, we will show the steps

Sandbox This sandbox contains code that is for various resons not ready to be included in statsmodels proper. It contains modules from the old stats.models code that

ANOVA Analysis of Variance models Examples In [1]: import statsmodels.api as sm In [2]: from

endog, exog, what?s that? Statsmodels is using endog and exog as names for the data, the observed variables that are

Input-Output iolib statsmodels offers some functions for input and output. These include a reader for STATA files, a class for generating

Tools Our tool collection contains some convenience functions for users and functions that were written mainly for internal use. Additional to this tools directory

Weight Functions Andrew?s Wave Hampel

Distributions This section collects various additional functions and methods for statistical distributions. Empirical

Time Series analysis tsa statsmodels.tsa contains model classes and functions that are useful for time series analysis. This currently

Generalized Estimating Equations Generalized Estimating Equations estimate generalized linear models for panel, cluster or repeated measures