[R] Multi-dimensional non-linear fitting - advice on best method?
pdalgd at gmail.com
Mon Apr 25 00:57:46 CEST 2011
On Apr 24, 2011, at 02:38 , Julian Gilbey 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.
> Many thanks,
> R-help at r-project.org mailing list
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> and provide commented, minimal, self-contained, reproducible code.
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