statsmodels.gam.generalized_additive_model.GLMGam.information

GLMGam.information(params, scale=None)

Fisher information matrix.

Returns -1 * Hessian of the log-likelihood evaluated at params, i.e. the expected information matrix, which is positive definite.

Parameters:

paramsndarray

Parameter at which the information is evaluated.

scalefloat, optional

If scale is None, then the default scale will be calculated. Default scale is defined by self.scaletype and set in fit. If scale is not None, then it is used as a fixed scale.

Returns:

ndarray

The expected information matrix, X' W X / scale. This is -hessian(params, scale, observed=False). It differs from -hessian(params, scale), which is the observed information by default, unless the link is the canonical link of the family.