Hessian in Optmum and Constrained Optmum

Hallo!

 

I am working in Gauss 12 with Optmum module and I need to estimate the variance-covariance matrix. I wanted to take th inverse of the final Hessian calculated by Optmum, or just to take the inverse of  _opfhess.

I tried and the results are too small, so I wonder that probably the entries of the Hessian matrix are multiplied by the number of observations?

Should I first to correct and divide my Hessian by the number of observations and only afterwards to take the inverse?

I tried to find the information in the manuals but I couldn't.

Thank you a lot in advance!

Aygul

1 Answer



0



The Optmum examples, opt2.e and opt4.e show how to compute the covariance matrix of the parameters using the cross-product of the gradient matrix.  You could also compute the Hessian using the hessp() function in the Run-Time Library.  The final approximations from the iterations is not good enough for a covariance matrix.  It's available primarily for diagnosing convergence problems.

Your Answer

1 Answer

0

The Optmum examples, opt2.e and opt4.e show how to compute the covariance matrix of the parameters using the cross-product of the gradient matrix.  You could also compute the Hessian using the hessp() function in the Run-Time Library.  The final approximations from the iterations is not good enough for a covariance matrix.  It's available primarily for diagnosing convergence problems.


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