I tried to ?ms, ?nls and apparently these aren't implemented on R yet. However I seem to remember postings on this list having to do with fitting nonlinear models (no I don't mean GLM type fits, I have a REAL nonlinear model: y=ax^b + c). So please tell me if it is possible to fit nonlinear models in R (by least squares or ML). Thanks! Bill Simpson -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
Bill Simpson <wsimpson at uwinnipeg.ca> writes:> I tried to ?ms, ?nls and apparently these aren't implemented on R yet. > However I seem to remember postings on this list having to do with fitting > nonlinear models (no I don't mean GLM type fits, I have a REAL nonlinear > model: y=ax^b + c). So please tell me if it is possible to fit nonlinear > models in R (by least squares or ML).There is the nlm function in R for general unconstrained optimization. Its syntax is different from that of ms in S so you have to do a bit of work to map from one to the other. In some ways the scoping rules of R make it much easier to do nonlinear optimization than in S. As for nls I would like to re-think the approach to nonlinear least squares in S-like languages and come up with a version that could be used either in R or in S. That's on the "To Do" list but that list is pretty long so don't hold your breath. If some enterprising person wanted to work on it I would be delighted to offer sage advice. I always wanted to be a sage and now that my hair is all gray ... -- Douglas Bates bates at stat.wisc.edu Statistics Department 608/262-2598 University of Wisconsin - Madison http://www.stat.wisc.edu/~bates/ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._