[R] nls - find good starting values

[Antje]

Hi there,

it might be a very simple question and I'd be glad to even get a link to 
some useful documentation...
I have several data sets, I'd like to fit to a gaussian distribution. 
I've tried to give an estimate of the mean and the sd of this 
distribution but still, I run into problems if these estimates are not 
close enough.

For example, nls() breaks with this message:
singular gradient matrix at initial parameter estimates

I don't know how to avoid these bad start values because their estimate 
is automated. Better start values are often quite close.

I was wondering whether there is any way to test several start-values as 
long as nls does not succeed.
I would do it with a while construct but maybe there is another approach?

Any hint is very welcome!

Ciao,
Antje