error estimation in a non-linear least squares fitting

[Evelien]

Dear python-users,

I am trying to do a non-linear least squares fitting. Maybe trying is
not the best word, as I already succeeded in that. At the moment I am
using leastSquaresFit from Scientific Python. I know of other least
squares routines, such as the one in scipy.optimize and I believe
there is also one in numpy. Now here is my question: in my search for
a good algorithm, I was not able to find any non-linear least squares
fitting routine which in the end doesn't only give me the parameters
which I asked for, but also the estimated errors on these parameters.
Is there anyone who can help me getting these errors?

Thanks in advance,
Evelien