[R] nls fits by groups

[Gabor Grothendieck]

Check out the subset= argument to nls, e.g. to regress Sepal.Length
on Sepal.Width separately for each Species using the built in iris data set:

f <- function(s) nls(Sepal.Length ~ a*Sepal.Width, data = iris,
   start = c(a = 1), subset = iris$Species == s)
sapply(levels(iris$Species), f, simplify = FALSE)


On 9/23/07, Aleksi Lehtonen <lehtonen.aleksi at gmail.com> wrote:
> Dear Colleagues,
>
> I am trying to estimate several non-linear models simultaneously. I don't
> want to use non-linear mixed model, but non-linear model with same form, but
> it should be estimated separately according to variable group (I have lots
> of groups that have lots of observations....). I would like to have unique
> parameters for each group.
>
> e.g. something like this
>
> mod <- nls(y ~ a*x^b, start=c(a=1, b=1), group=group)
>
> but knowing that group option does not work. If someone has an idea (or has
> done it already) how to implement this either using just nls statement or by
> building a simple function in R, I would be very grateful for hints....
>
> regards, Aleksi Lehtonen
>
>        [[alternative HTML version deleted]]
>
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