GLM.score_test()

statsmodels.genmod.generalized_linear_model.GLM.score_test

GLM.score_test(params_constrained, k_constraints=None, exog_extra=None, observed=True) [source]

score test for restrictions or for omitted variables

The covariance matrix for the score is based on the Hessian, i.e. observed information matrix or optionally on the expected information matrix..

Parameters:

params_constrained : array_like estimated parameter of the restricted model. This can be the parameter estimate for the current when testing for omitted variables. k_constraints : int or None Number of constraints that were used in the estimation of params restricted relative to the number of exog in the model. This must be provided if no exog_extra are given. If exog_extra is not None, then k_constraints is assumed to be zero if it is None. exog_extra : None or array_like Explanatory variables that are jointly tested for inclusion in the model, i.e. omitted variables. observed : bool If True, then the observed Hessian is used in calculating the covariance matrix of the score. If false then the expected information matrix is used.

Returns:

chi2_stat : float chisquare statistic for the score test p-value : float P-value of the score test based on the chisquare distribution. df : int Degrees of freedom used in the p-value calculation. This is equal to the number of constraints.

Notes

not yet verified for case with scale not equal to 1.