code: def _forecast_model(self,beta,Z,h):
               
  
          T, _, R, Q, H = self._ss_matrices(beta)
          return dl_univariate_kalman_fcst(self.data,Z,H,T,Q,R,0.0,h)
docs: Creates forecasted states and variances
  
          Parameters
          ----------
          beta : np.ndarray
              Contains untransformed starting values for latent variables
  
          Returns
          ----------
          a : np.ndarray
              Forecasted states
  
          P : np.ndarray
              Variance of forecasted states