code: def posteriori_mean(self):
          r
          from numpy_sugar.linalg import rsolve
  
          Sigma = self.posteriori_covariance()
          eta = self._ep._posterior.eta
          return dot(Sigma, eta + rsolve(GLMM.covariance(self), self.mean()))
docs: r""" Mean of the estimated posteriori.
  
          This is also the maximum a posteriori estimation of the latent variable.