Generalized Linear Models

Generalized Linear Models

Generalized linear models currently supports estimation using the one-parameter exponential families

See Module Reference for commands and arguments.

Examples

# Load modules and data
import statsmodels.api as sm
data = sm.datasets.scotland.load()
data.exog = sm.add_constant(data.exog)

# Instantiate a gamma family model with the default link function.
gamma_model = sm.GLM(data.endog, data.exog, family=sm.families.Gamma())
gamma_results = gamma_model.fit()

Detailed examples can be found here:

• Generalized Linear Models
• Generalized Linear Models (Formula)

Technical Documentation

References

• Gill, Jeff. 2000. Generalized Linear Models: A Unified Approach. SAGE QASS Series.
• Green, PJ. 1984. ?Iteratively reweighted least squares for maximum likelihood estimation, and some robust and resistant alternatives.? Journal of the Royal Statistical Society, Series B, 46, 149-192.
• Hardin, J.W. and Hilbe, J.M. 2007. ?Generalized Linear Models and Extensions.? 2nd ed. Stata Press, College Station, TX.
• McCullagh, P. and Nelder, J.A. 1989. ?Generalized Linear Models.? 2nd ed. Chapman & Hall, Boca Rotan.

Module Reference

Model Class

Results Class

Families

The distribution families currently implemented are

Link Functions

The link functions currently implemented are the following. Not all link functions are available for each distribution family. The list of available link functions can be obtained by

>>> sm.families.family.<familyname>.links