Hi, thank you for your very nice work to port this algorithm to C++.
Would it be possible to add a method to get the final approximated covariance matrix of the parameters, ie the inverse Hessian, like for instance the final_grad does for the final gradiant of the objective function ? The scipy implementation have this capability.
Hi, thank you for your very nice work to port this algorithm to C++.
Would it be possible to add a method to get the final approximated covariance matrix of the parameters, ie the inverse Hessian, like for instance the final_grad does for the final gradiant of the objective function ? The scipy implementation have this capability.