Hi,
You could use another package, like openopt and the generic optimizers that
give you what you want provided that you create at least the gradient of
the function (I didn't create a class that can numerically derive a fit
function).
For instance
http://projects.scipy.org/scipy/scikits/wiki/Optimization/tutorial#FittingDatagives
you an example.
Matthieu
2007/12/6, Ping Yeh <[EMAIL PROTECTED]>:
>
> Hi,
>
> I have (x,y) data that I want to fit to the formula
> y = a * x^b
> to determine a and b. How can I do it? The current
> manual only lists linear fit and polynomial fit.
>
> Or, putting it in a more general setting, is there a
> module to do fitting to an arbitrary function?
> It would be something like
>
> pars = fit(x, y, func)
>
> where func is a function like
>
> y = func(x, pars)
>
> with pars a 1-D array.
>
> Thanks,
> Ping
>
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