statsmodels.genmod.generalized_linear_model.GLMResults.plot_added_variable

GLMResults.plot_added_variable(focus_exog, resid_type=None, use_glm_weights=True, fit_kwargs=None, ax=None)

Create an added variable plot for a fitted regression model.

Parameters:

focus_exog : int or string

The column index of exog, or a variable name, indicating the variable whose role in the regression is to be assessed.

resid_type : string

The type of residuals to use for the dependent variable. If None, uses resid_deviance for GLM/GEE and resid otherwise.

use_glm_weights : bool

Only used if the model is a GLM or GEE. If True, the residuals for the focus predictor are computed using WLS, with the weights obtained from the IRLS calculations for fitting the GLM. If False, unweighted regression is used.

fit_kwargs : dict, optional

Keyword arguments to be passed to fit when refitting the model.

ax : Axes instance

Matplotlib Axes instance

Returns:

fig : matplotlib Figure

A matplotlib figure instance.