In case anyone is still reading this thread, I want to add this: In a current problem (a data-shy five-parameter nonlinear optimization), I found "nlminb" markedly more reliable than "optim" with method "L-BFGS-B". In reviewing the fit I made, I found that "optim" only came close to its own minimum in about 13 of 120 trials (same data, different starting values). I previously said 97, but I was clearly looking at the wrong data! In contrast, "nlminb" came to that best answer in about 92 trials out of 120.
The original poster might consider "nlminb" instead of "optim". Because nonlinear optimization is sensitive to starting values, I would still advise solving the problem a number of times to see if a clear minimum solution emerges. -- Mike Prager, NOAA, Beaufort, NC * Opinions expressed are personal and not represented otherwise. * Any use of tradenames does not constitute a NOAA endorsement. ______________________________________________ R-help@r-project.org mailing list 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.
