On Mon, Apr 25, 2011 at 12:57:46AM +0200, peter dalgaard wrote: > > 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.
Will take a look, 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.
