[R] Fitting 2D vs. 2D data with nls()

[Timur Elzhov]

On Fri, Dec 06, 2002 at 01:57:28PM -0500, Warnes, Gregory R wrote:

> > Actually I want to fit y[,1] ~ x[,1] and y[,2] ~ x[,2]
> > *simulaneously*, with the same parameters set {p1, p2, p3}.
> Do you want to get separate estimates of p1, p2, and p3:
> 
> 	one set for y[,1] ~ x[,1] and a separate set for y[,2] ~ x[,2], 
> 
> or do you want to get 3 common parameter values?
> 
> For the latter, just do
> 
> fit.result <- nls ( as.vector(y) ~ f(as.vector(x), p1, p2, p3),
>                     start = list(p1 = ... , p2 = .. , p3 = ..)
> 
Yes! that is answer to question I posted! :-)
But.. I was actually wrong a bit, the situation is more
complicated:
I want *some* of the parameters to have common values,
and to be estimated seperately -- for the rest..

Thank you for your answer anyway, I couldn't guess
that simple solution even for common parameters.


WBR,
Timur