statsmodels.gam.generalized_additive_model.GLMGamResults.predict

GLMGamResults.predict(exog=None, exog_smooth=None, transform=True, **kwargs)[source]

” compute prediction

Parameters

exog : array_like, optional

The values for the linear explanatory variables

exog_smooth : array_like

values for the variables in the smooth terms

transform : bool, optional

If transform is True, then the basis representation of the smooth term will be constructed from the provided exog.

kwargs :

Some models can take additional arguments or keywords, see the predict method of the model for the details.

Returns

prediction : ndarray, pandas.Series or pandas.DataFrame

predicted values