As an additional note, the parscale argument can be useful to improve stability in convergence results in optim().
Chris ----------------------------- Chris Gast cmg...@gmail.com On Thu, Jun 17, 2010 at 1:32 PM, Chris Gast <cmg...@gmail.com> wrote: > I spoke with my colleague who did most of the testing, and he has informed > me that much of the hessian sensitivity actually came from a separate > program (based on Numerical Recipes in C++ code) that did not use optim(), > after having stopped using optim() due to speed issues. > > In my experience with optim, the reltol argument has improved important in > this regard. Very small changes in the parameter estimates at the converged > solution (influenced by reltol) can lead to different standard error > estimates by inverting the hessian, especially for parameter estimates close > to zero (as vulnerability coefficients can be in many models with such a > feature). It is a limitation of the finite difference method for computing > the hessian based on optimal parameter estimates. > > > > Chris > > > > ----------------------------- > Chris Gast > cmg...@gmail.com > > > > On Wed, Jun 16, 2010 at 11:05 PM, Rubén Roa <r...@azti.es> wrote: > >> ________________________________ >> >> De: users-boun...@admb-project.org [mailto:users-boun...@admb-project.org] >> En nombre de Chris Gast >> Enviado el: miércoles, 16 de junio de 2010 21:11 >> Para: Arni Magnusson >> CC: r-help@r-project.org; us...@admb-project.org >> Asunto: Re: [ADMB Users] an alternative to R for nonlinear stat models >> >> Hi Arni (and others), >> My dissertation work involves use (and extension) of models of the same >> ilk (sometimes exactly the same) as those described by Nancy Gove and John >> Skalski in their 2002 article. I began with R, and moved to my own >> home-brewed C/C++ programs for the sake of of speed when fitting models and >> real and simulated data. In addition, we found that the estimated standard >> errors (based on the inverse hessian output from optim()) were very >> sensitive to tolerance criteria--often changing orders of magnitude. >> >> >> Hi, >> Regarding the last bit, optim() has several methods (Nelder-Mead, >> simulated annealing, conjugate gradient, etc). It is interesting to me which >> method produced what result with the standard errors from the inverse >> Hessian. Can you briefly ellaborate? >> Thanks >> Rubén >> >> >> ____________________________________________________________________________________ >> >> Dr. Rubén Roa-Ureta >> AZTI - Tecnalia / Marine Research Unit >> Txatxarramendi Ugartea z/g >> 48395 Sukarrieta (Bizkaia) >> SPAIN >> >> > [[alternative HTML version deleted]]
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