statsmodels.gam.generalized_additive_model.LogitGam.fit¶

LogitGam.fit(method=None, trim=None, **kwds)¶

minimize negative penalized log-likelihood

Parameters:¶

methodNone or str

Method specifies the scipy optimizer as in nonlinear MLE models.

trim{bool, float}

Default is False or None, which uses no trimming. If trim is True or a float, then small parameters are set to zero. If True, then a default threshold is used. If trim is a float, then it will be used as threshold. The default threshold is currently 1e-4, but it will change in future and become penalty function dependent.

kwdsextra keyword arguments

This keyword arguments are treated in the same way as in the fit method of the underlying model class. Specifically, additional optimizer keywords and cov_type related keywords can be added.