def deviance(self, endog, mu, freq_weights=1., scale=1.):
        r"""
        Gaussian deviance function

        Parameters
        ----------
        endog : array-like
            Endogenous response variable
        mu : array-like
            Fitted mean response variable
        freq_weights : array-like
            1d array of frequency weights. The default is 1.
        scale : float, optional
            An optional scale argument. The default is 1.

        Returns
        -------
        deviance : float
            The deviance function at (endog,mu,freq_weights,scale)
            as defined below.

        Notes
        --------
        .. math::

           D = \sum_i freq\_weights_i * (Y_i - \mu_i)^2 / scale
        """
        return np.sum((freq_weights * (endog - mu)**2)) / scale
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/genmod/families/family.py/Gaussian.deviance/original