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st: Is it possible to use Nelder Mead optimization with ml


From   "Woodruff, Robert T" <WOODRUFFR@battelle.org>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: Is it possible to use Nelder Mead optimization with ml
Date   Thu, 19 Apr 2012 12:23:06 -0400

Hello all,

I wrote an --ml-- d0 program to optimize a conditional likelihood that is a nonlinear function of the parameters.  I'm using a stereotype regression model for a matched case-control study (and hence couldn't use the existing implementations for unconditional stereotype models).  For the most part it works fine but for some datasets it has a tough time with convergence.  I've played around with the different optimization options (except BHHH) and initial values but it can't seem to find the top of the hill.  I know Nelder-Mead has been implemented in Mata's --moptimize-- function but I was wondering if anyone knew if I can use it with --ml-- too.  

Also, I can compute the gradient and Hessian explicitly but currently am being lazy by just letting --ml-- compute them numerically.  Do you think this would make much of a difference for the methods that use the derivatives?

Thanks,
Rob Woodruff
woodruffr@battelle.org

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