statsmodels.gam.generalized_additive_model.GLMGam.fit

GLMGam.fit(start_params=None, maxiter=1000, method='pirls', tol=1e-08, scale=None, cov_type='nonrobust', cov_kwds=None, use_t=None, full_output=True, disp=False, max_start_irls=3, **kwargs)

estimate parameters and create instance of GLMGamResults class

Parameters:

most parameters are the same as for GLM

methodoptimization method

The special optimization method is “pirls” which uses a penalized version of IRLS. Other methods are gradient optimizers as used in base.model.LikelihoodModel.

Returns:

resinstance of wrapped GLMGamResults