Returns Markov blanket of the states given the variance latent variables

        Parameters
        ----------
        beta : np.array
            Contains untransformed starting values for latent variables

        alpha : np.array
            State matrix

        Returns
        ----------
        State likelihood

def state_likelihood_markov_blanket(self, beta, alpha, col_no):
        """ Returns Markov blanket of the states given the variance latent variables

        Parameters
        ----------
        beta : np.array
            Contains untransformed starting values for latent variables

        alpha : np.array
            State matrix

        Returns
        ----------
        State likelihood
        """     
        _, _, _, Q = self._ss_matrices(beta)
        blanket = np.append(0,ss.norm.logpdf(alpha[col_no][1:]-alpha[col_no][:-1],loc=0,scale=np.sqrt(Q[col_no][col_no])))
        blanket[:-1] = blanket[:-1] + blanket[1:]
        return blanket