Returns likelihood 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(self, beta, alpha):
        """ Returns likelihood 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)
        state_lik = 0
        for i in range(alpha.shape[0]):
            state_lik += np.sum(ss.norm.logpdf(alpha[i][1:]-alpha[i][:-1],loc=0,scale=np.power(Q[i][i],0.5))) 
        return state_lik