Creates approximating Gaussian state space model for Skewt measurement density
        
        Parameters
        ----------
        beta : np.array
            Contains untransformed starting values for latent variables
        
        T, Z, R, Q : np.array
            State space matrices used in KFS algorithm
        
        h_approx : float
            The variance of the measurement density
        
        data: np.array
            The univariate time series data

        X: np.array
            The regressors

        state_no : int
            Number of states
    
        Returns
        ----------
        H : np.array
            Approximating measurement variance matrix
        
        mu : np.array
            Approximating measurement constants

def approximating_model_reg(self, beta, T, Z, R, Q, h_approx, data, X, state_no):
        """ Creates approximating Gaussian state space model for Skewt measurement density
        
        Parameters
        ----------
        beta : np.array
            Contains untransformed starting values for latent variables
        
        T, Z, R, Q : np.array
            State space matrices used in KFS algorithm
        
        h_approx : float
            The variance of the measurement density
        
        data: np.array
            The univariate time series data

        X: np.array
            The regressors

        state_no : int
            Number of states
    
        Returns
        ----------
        H : np.array
            Approximating measurement variance matrix
        
        mu : np.array
            Approximating measurement constants
        """     

        H = np.ones(data.shape[0])*h_approx
        mu = np.zeros(data.shape[0])

        return H, mu