Thanks a lot Spencer for your tips - I'll look into all of them. Rainer
Spencer Graves wrote: > It's difficult to say much at this level of generality, but I have > four suggestions: > > 1. Have you tried creating a reasonable grid of starting values > using "expand.grid" and then plotting the resulting likelihood surface? > If you have more than 2 parameters, you may want to use 'lattice' > graphics. This should tell you if the functions seems unimodal, convex, > etc., in the region you covered and at the resolution of your grid. > > 2. Have you tried method="SANN" = simulated annealing? I might > try one pass with SANN, then refine the solution found by SANN using BFGS. > > 3. After you have a solution, you can then try profile likelihod. > Unfortunately, my experience with profile.mle has been mixed. I > actually made local copies of mle and profile.mle and found and fixed > some of the deficiencies of each. I didn't test them enough to offer > the results to the R Core Team, however. > > 4. Have you looked at Venables and Ripley (2002) Modern Applied > Statistics with S, 4th ed. (Springer)? It's a great book for many > things, including the use of expand.grid and 'optim'. > > hope this helps. > Spencer Graves > > Rainer M Krug wrote: >> Hi >> >> I hope this is the right forum - if not, point me please to a better one. >> >> I am using R 2.3.0 on Linux, SuSE 10. >> >> >> I have a question concerning mle (method="BFGS"). >> >> I have a few models which I am fitting to existing data points. I >> realised, that the likelihood is quite sensitive to the start values for >> one parameter. >> >> I am wondering: what is the best approach to identify the right initial >> values? Do I have to do it recursively, and if yes, how can I automate >> it? Or do I have to play with the system? >> >> I am quite confident that the resulting parameters are the optimal for >> my problem - but can I verify it? >> >> Thanks, >> >> Rainer >> >> -- Rainer M. Krug, Dipl. Phys. (Germany), MSc Conservation Biology (UCT) Department of Conservation Ecology and Entomology University of Stellenbosch Matieland 7602 South Africa ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
