[Help-gsl] ways to change sensitivity of the Le venberg–Marquardt solver to the initial guess

[Soren Christensen]

Hi,
 I have a 4 parameter function that I try to fit to data. I am using
the nmsimplex minimizer which works very well, but to improve speed I
wanted to use the 'lmsder' fitter in stead.
For no-noise data and perfect start guesses, both implementations fit
perfectly (you should hope so). When changing the guess just slightly
the lmsder fitter fails, whereas the simplex routine is robust for
much larger differences between the initial guess and the solution.
What can I do to improve the performance of the lmsder - is there any
tuning I can do to my function or the solver?  (Improving the guess to
what appears to be required from lmsder will not be possible).

Thanks in advance,
Soren