statsmodels.gam.generalized_additive_model.LogitGam.fit

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

minimize negative penalized log-likelihood

Parameters:

method : None 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.

kwds : extra 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.