Hi, It seems to me that the most suitable method in R for curve-fitting is the use of nls, which uses a Gauss-Newton (GN) algorithm, while the use of the Levenberg-Marquardt (LM) algorithm does not seem to be very stressed in R. According to this [1] by Ripley, 'Levenberg-Marquardt is hardly competitive these days' which could imply the low emphasize on LM in R.
The position of LM is, to some extend, confusing. Bonnans et al [2] introduce the trust-region-based method of LM like this: 'This chapter is mostly devoted to methods which, although less "universal" than the preceding, are useful in a good number of cases. The frst one (trust-region) is actually extremely important, and might supersede line-searches, sooner or later.' The above should demonstrate the contradiction. Since some R developers are indeed the pioneers in the optimisation theory, I would like to ask for references involving profiling of various methods, including more modern techniques, with an application in general model-fitting. [1] http://tolstoy.newcastle.edu.au/R/help/00b/2492.html [2] Numerical Optimization, 2nd ed _________________________________________________________________ 100’s of Music vouchers to be won with MSN Music ______________________________________________ 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.
