code: def normal_neg_loglik(self, beta):
               
          mu, Y = self._model(beta)
          return -np.sum(ss.norm.logpdf(Y, loc=mu, scale=self.latent_variables.z_list[-1].prior.transform(beta[-1])))
docs: Calculates the negative log-likelihood of the model for Normal family
  
          Parameters
          ----------
          beta : np.ndarray
              Contains untransformed starting values for latent variables
  
          Returns
          ----------
          The negative logliklihood of the model