glm mean function, ie inverse of link function
        this is useful for going from the linear prediction to mu

        Parameters
        ----------
        lp : array-like of legth n
        dist : Distribution instance

        Returns
        -------
        mu : np.array of length n

def mu(self, lp, dist):
        """
        glm mean function, ie inverse of link function
        this is useful for going from the linear prediction to mu

        Parameters
        ----------
        lp : array-like of legth n
        dist : Distribution instance

        Returns
        -------
        mu : np.array of length n
        """
        elp = np.exp(lp)
        return dist.levels * elp / (elp + 1)