> > I'm wondering about experiences: > Do you know of cases where minpack.lm's nls.lm() solved a > (real) problem that nls() would have a problem with ? >
In short, no. However, I looked at this question in the limited context of fitting the parameters of a linear superposition of 2 exponentials with Gaussian noise. A simulation study showed nearly identical performance for the range of parameter values/noise levels that are of practical interest to us. Are there problems for which steepest descent gets you in the neighborhood of a solution whereas GN does not? If such problems exist then there would be reason to apply LM instead of GN, but I don't know of any. > Beware however -- one of the main things I learned about this > field from Doug Bates, co-author of Bates_and_Watts and > prinicipal author of S's and R's nls() : > It's a *feature* that nls() does not converge sometimes when > other methods do falsely claim convergence! > > Martin Maechler, ETH Zurich > > KateM> ---- > KateM> Katharine Mullen > KateM> mail: Department of Physics and Astronomy, Faculty of Sciences > KateM> Vrije Universiteit Amsterdam, de Boelelaan 1081 > KateM> 1081 HV Amsterdam, The Netherlands > KateM> room: T.1.06 > KateM> tel: +31 205987870 > KateM> fax: +31 205987992 > KateM> e-mail: [EMAIL PROTECTED] > KateM> homepage: http://www.nat.vu.nl/~kate/ > > > KateM> On Fri, 7 Sep 2007, Jose Luis Aznarte M. wrote: > > >> Hi! I'm translating some code from Matlab to R and I found a problem. > >> I need to translate Matlab's function 'lsqnonlin' > >> (http://www-ccs.ucsd.edu/matlab/toolbox/optim/lsqnonlin.html) into R, > >> and at the beginning I thought it would be the same as R's 'optim'. > But > >> then I looked at the definition of 'lsqnonlin' and I don't quite see > how > >> to make 'optim' to do the same thing. Does anyone have an idea? > >> This is apart from the fact that I would like to use the Levenberg > >> Marquardt algorithm which is not implemented in R (some discussion > about > >> this: http://tolstoy.newcastle.edu.au/R/help/00b/2492.html). > >> Thank you! All the best, > >> > >> > >> -- -- > >> Jose Luis Aznarte M. http://decsai.ugr.es/~jlaznarte > >> Department of Computer Science and Artificial Intelligence > >> Universidad de Granada Tel. +34 - 958 - 24 04 67 > >> GRANADA (Spain) Fax: +34 - 958 - 24 00 79 > >> > >> ______________________________________________ > >> R-help@stat.math.ethz.ch 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. > >> > > KateM> ______________________________________________ > KateM> R-help@stat.math.ethz.ch mailing list > KateM> https://stat.ethz.ch/mailman/listinfo/r-help > KateM> PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > KateM> and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@stat.math.ethz.ch 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.