Robust Linear Models

Robust Linear Models

Robust linear models with support for the M-estimators listed under Norms.

See Module Reference for commands and arguments.

Examples

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

# Fit model and print summary
rlm_model = sm.RLM(data.endog, data.exog, M=sm.robust.norms.HuberT())
rlm_results = rlm_model.fit()
print rlm_results.params

Detailed examples can be found here:

• Robust Linear Models
• M-Estimators for Robust Linear Modeling

Technical Documentation

• Weight Functions

References

• PJ Huber. ?Robust Statistics? John Wiley and Sons, Inc., New York. 1981.
• PJ Huber. 1973, ?The 1972 Wald Memorial Lectures: Robust Regression: Asymptotics, Conjectures, and Monte Carlo.? The Annals of Statistics, 1.5, 799-821.
• R Venables, B Ripley. ?Modern Applied Statistics in S? Springer, New York,

Module Reference

Model Classes

Model Results

Norms

Scale