optim() problem

I am trying to fit a exponential power distribution

y = b/(2*pi*a^2*gamma(2/b))*exp(-(x/a)^b)

to a bunch of data for x and y I have in a table.

data

           x         y
1         25        27
2         75        59
3        125       219
...
259    12925         1
260    12975         0

I know "optim" should do a minimisation, therefor I used as the
optimisation function

opt.power <- function(val, x, y) {
   a <- val[1];
   b <- val[2];
   sum(y - b/(2*pi*a^2*gamma(2/b))*exp(-(x/a)^b));
}

I call: (with xm and ym the data from the table)

a1 <- c(0.2, 100)
opt <- optim(a1, opt.power, method="BFGS", x=xm, y=ym)

but no optimisation of the parameter in a1 takes place.
Any ideas?

As someone who had a big hand in creating BFGS, I'm guessing (and guessing
can be dangerous) that there is a bad scaling somewhere that simply
prevents progress because the numerical derivatives are not easy to
calculate in such situations. If you send me data off-line, I'll take a
look.

Have you checked that your function evaluates properly? Always a good idea.

For information, I'm working on trying to improve optim's capabilities and
user-friendliness to try to address some of the issues that arise. I
welcome input. In particular, Ravi Varadhan and I would like to develop a
method "GUIDED" to allow users a way to set up the calls so they are
sensible for their problems.

John Nash