Markov blanket for each likelihood term

        Parameters
        ----------
        y : np.ndarray
            univariate time series

        mean : np.ndarray
            array of location parameters for the Skew t distribution

        scale : float
            scale parameter for the Skew t distribution

        shape : float
            tail thickness parameter for the Skew t distribution

        skewness : float
            skewness parameter for the Skew t distribution

        Returns
        ----------
        - Markov blanket of the Skew t family

def markov_blanket(y, mean, scale, shape, skewness):
        """ Markov blanket for each likelihood term

        Parameters
        ----------
        y : np.ndarray
            univariate time series

        mean : np.ndarray
            array of location parameters for the Skew t distribution

        scale : float
            scale parameter for the Skew t distribution

        shape : float
            tail thickness parameter for the Skew t distribution

        skewness : float
            skewness parameter for the Skew t distribution

        Returns
        ----------
        - Markov blanket of the Skew t family
        """
        m1 = (np.sqrt(shape)*sp.gamma((shape-1.0)/2.0))/(np.sqrt(np.pi)*sp.gamma(shape/2.0))
        mean = mean + (skewness - (1.0/skewness))*scale*m1
        return Skewt.logpdf_internal(x=y, df=shape, loc=mean, gamma=skewness, scale=scale)