Getting started
  • References/Python/Statsmodels/Manual

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

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endog, exog, what’s that?
  • References/Python/Statsmodels/Manual

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

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Tools
  • References/Python/Statsmodels/Manual

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

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ANOVA
  • References/Python/Statsmodels/Manual

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

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Sandbox
  • References/Python/Statsmodels/Manual

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

2025-01-10 15:47:30
Input-Output iolib
  • References/Python/Statsmodels/Manual

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

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Weight Functions
  • References/Python/Statsmodels/Manual

Weight Functions Andrew?s Wave Hampel

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Distributions
  • References/Python/Statsmodels/Manual

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

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Generalized Method of Moments gmm
  • References/Python/Statsmodels/Manual

Generalized Method of Moments gmm statsmodels.gmm contains model classes and functions that are based on estimation with Generalized

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Other Models miscmodels
  • References/Python/Statsmodels/Manual

Other Models miscmodels statsmodels.miscmodels contains model classes and that do not yet fit into any other category, or are

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