code: def expected_values(self, beta):
               
  
          parm = np.array([self.latent_variables.z_list[k].prior.transform(beta[k]) for k in range(beta.shape[0])])
          L = self._L(parm)
          alpha = self._alpha(L)
          return np.dot(np.transpose(self.kernel.K(parm)), alpha)
docs: Expected values of the function given the covariance matrix and hyperparameters
          
          Parameters
          ----------
          beta : np.ndarray
              Contains untransformed values for latent variables
          
          Returns
          ----------
          The expected values of the function