code: def multivariate_neg_logposterior(self,beta):
          
  
          post = self.neg_loglik(beta)
          for k in range(0,self.z_no):
              if self.latent_variables.z_list[k].prior.covariance_prior is True:
                  post += -self.latent_variables.z_list[k].prior.logpdf(self.custom_covariance(beta))
                  break
              else:
                  post += -self.latent_variables.z_list[k].prior.logpdf(beta[k])
          return post
docs: Returns negative log posterior, for a model with a covariance matrix 
  
          Parameters
          ----------
          beta : np.array
              Contains untransformed starting values for latent_variables
  
          Returns
          ----------
          Negative log posterior