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