On Apr 24, 2011, at 02:38 , Julian Gilbey wrote: > Hello! > > I have a set of data of the form (x, y1, y2) where x is the > independent variable and (y1, y2) is the response pair. The model is > some messy non-linear function: > > (y1, y2) = f(x; param1, param2, ..., paramk) + (y1error, y2error) > > where the parameters param1, ..., paramk are to be estimated, and I'll > assume the errors to be normal for sake of simplicity. > > If there were only one response per input, I would use the nls() > function, but what can I do in this case?
I believe the gnls function in the nlme package is your friend. It's a bit involved but the basic idea is to stack the two response variables and use a weights argument with a varIdent structure with variance depending on whether it is a y1 or a y2 observation. You can also specify a within-pair correlation. > > Many thanks, > > Julian > > ______________________________________________ > 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. -- Peter Dalgaard Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ 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.
