def null_beta(self):
        """
        Optimal 𝜷 according to the marginal likelihood.

        It is compute by solving the equation ::

            (XᵀBX)𝜷 = XᵀB𝐲.

        Returns
        -------
        beta : ndarray
            Optimal 𝜷.
        """
        ETBE = self._ETBE
        yTBX = self._yTBX

        A = sum(i.XTBX for i in ETBE)
        b = sum(yTBX)
        return rsolve(A, b)
def null_beta(self):
        """
        Optimal 𝜷 according to the marginal likelihood.

        It is compute by solving the equation ::

            (XᵀBX)𝜷 = XᵀB𝐲.

        Returns
        -------
        beta : ndarray
            Optimal 𝜷.
        """
        ETBE = self._ETBE
        yTBX = self._yTBX

        A = sum(i.XTBX for i in ETBE)
        b = sum(yTBX)
        return rsolve(A, b)
def null_beta ( self ) : ETBE = self . _ETBE yTBX = self . _yTBX A = sum ( i . XTBX for i in ETBE ) b = sum ( yTBX ) return rsolve ( A , b )
Optimal 𝜷 according to the marginal likelihood.

        It is compute by solving the equation ::

            (XᵀBX)𝜷 = XᵀB𝐲.

        Returns
        -------
        beta : ndarray
            Optimal 𝜷.
Optimal 𝜷 according to the marginal likelihood .