The postings about polyalgorithms don't mention that optimx has a tool called polyopt() for this. Though I included it in the package, it has not been widely tested or applied, and more experience with such approaches would certainly be of interest to a number of workers, though I suspect the results are rather context-dependent.
JN On 2018-12-01 3:52 a.m., Jeremie Juste wrote: > > Hello, > > Genetic algorithm can prove handy as well here. see for instance > https://cran.r-project.org/web/packages/GA/vignettes/GA.html > > with non-convex objective functions I usually try a genetic algorithm for > a few rounds then finish using nlminb > > > Best regards, > Jeremie > > Marc Girondot via R-help <r-help@r-project.org> writes: > >> I fit also model with many variables (>100) and I get good result when >> I mix several method iteratively, for example: 500 iterations of >> Nelder-Mead followed by 500 iterations of BFGS followed by 500 >> iterations of Nelder-Mead followed by 500 iterations of BFGS >> etc. until it stabilized. It can take several days. >> I use or several rounds of optimx or simply succession of optim. >> >> Marc >> >> Le 28/11/2018 à 09:29, Ruben a écrit : >>> Hi, >>> >>> Sarah Goslee (jn reply to Basic optimization question (I'm a >>> rookie)): "R is quite good at optimization." >>> >>> I wonder what is the experience of the R user community with high >>> dimensional problems, various objective functions and various >>> numerical methods in R. >>> >>> In my experience with my package CatDyn (which depends on optimx), I >>> have fitted nonlinear models with nearly 50 free parameters using >>> normal, lognormal, gamma, Poisson and negative binomial exact >>> loglikelihoods, and adjusted profile normal and adjusted profile >>> lognormal approximate loglikelihoods. >>> >>> Most numerical methods crash, but CG and spg often, and BFGS, >>> bobyqa, newuoa and Nelder-Mead sometimes, do yield good results (all >>> numerical gradients less than 1) after 1 day or more running in a >>> normal 64 bit PC with Ubuntu 16.04 or Windows 7. >>> >>> Ruben >>> >> >> ______________________________________________ >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.