The proposed Hessian approximation can be combined with other techniques, such as Laplace approximation or variational inference, to further enhance the estimation accuracy and robustness. Laplace approximation, which approximates the posterior distribution with a Gaussian centered at the mode, can benefit from the more accurate Hessian provided by the Hessian-Sum-Mixture method. By incorporating the precise curvature information from the Hessian, the Laplace approximation can better capture the shape of the posterior distribution, leading to more accurate estimates. Similarly, variational inference, which approximates the posterior with a simpler distribution, can leverage the improved Hessian to refine its approximation and provide more reliable estimates of the state variables. By combining the proposed Hessian approximation with these techniques, the overall estimation accuracy and robustness can be significantly improved.