R help - Sep 2006 - starting point for non linear fitting

Hi all!
 i'm trying to use nls for fitting my data. I wrote this code to find
some minimum, but it fails, returning 0 every time..... and i can't
figure out the problem... any advice?

grid <- expand.grid(A0 = seq(1000,10000,1000), A1 = seq(0,2,0.1))
exp.approx <- function(x,A0,A1) {
  A0 * exp(- x*A1)
}
ss <- function(p) {
                   sum((durata.h.freq - exp.approx(durata.h.x,p[0],p[1]))^2)}

idx <- which.min(apply(grid,1,ss))



idx is always 1,1... and that's not true...

"nelson -" <nelson1977 at gmail.com> writes:
> Hi all!
>  i'm trying to use nls for fitting my data. I wrote this code to find
> some minimum, but it fails, returning 0 every time..... and i can't
> figure out the problem... any advice?
> 
> grid <- expand.grid(A0 = seq(1000,10000,1000), A1 = seq(0,2,0.1))
> exp.approx <- function(x,A0,A1) {
>   A0 * exp(- x*A1)
> }
> ss <- function(p) {
>                    sum((durata.h.freq -
exp.approx(durata.h.x,p[0],p[1]))^2)}
> 
> idx <- which.min(apply(grid,1,ss))
> 
> 
> 
> idx is always 1,1... and that's not true...
Array indexing in R is 1-based, so p[0] is asking for trouble....

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