def _estimate_p_values(self):
        """estimate the p-values for all features
        """
        if not self._is_fitted:
            raise AttributeError('GAM has not been fitted. Call fit first.')

        p_values = []
        for term_i in range(len(self.terms)):
            p_values.append(self._compute_p_value(term_i))

        return p_values
def _estimate_p_values ( self ) : if not self . _is_fitted : raise AttributeError ( 'GAM has not been fitted. Call fit first.' ) p_values = [ ] for term_i in range ( len ( self . terms ) ) : p_values . append ( self . _compute_p_value ( term_i ) ) return p_values
estimate the p-values for all features