Thanks Ben, John, Richard You confirm my experience: above certain amount of RAM there are no improvements in speed. It cost me 3K euros to learn that, but the machine will be good for image processing. So for largish nonlinear models, over a 100 parameters, optimization in R would best be done with analytical gradients or by calling code written in C++ (autodiff TMB or ADMB) or FORTRAN. It seems to be the best option, as parallelization of computations with the obj. function would be entering unknown territory. For intermediate problems with 50-100 parameters, even a laptop with 36 GB RAM finish in a few hours, which is good enough for me. Regards. R.
--- Ruben H. Roa-Ureta, Ph. D. Consultant in Statistical Modeling ORCID ID 0000-0002-9620-5224 ______________________________________________ [email protected] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide https://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
