On Jul 19, 2006, at 16:53, Harold Fellermann wrote:
> :-) Anyway, I had
> the impression that the leastSquaresFit in Scientific Python is an
> implementation of
> the Levenberg Marquardt algorithm as it is presented in the Numerical
> Recipes.
True.
> Accoring
> to reviews, this algorithm is not
Thanks for your advices, Terry and Konrad,
using the linear fit as initial condition for the pawerlow fit works
pretty well for my data.
(I already had the two calculations but performed them vice versa ...
:-) Anyway, I had
the impression that the leastSquaresFit in Scientific Python is an
implem
On 18.07.2006, at 15:59, Harold Fellermann wrote:
def powerlaw((a,b),x) :
> ... return a*x**b
Fitting power laws is a tricky business, you need a pretty good
initial guess to get convergence.
> Note that I could easily fit the above data using gnuplots internal
> fitting procedure. An
"Harold Fellermann" <[EMAIL PROTECTED]> wrote in message
news:[EMAIL PROTECTED]
> I am trying to fit a powerlaw to a small dataset using
> Scientific.Functions.LeastSquares fit.
This is a bit off-topic here, and normally better for the scipy list, but I
have some experience with nonlinear least
Dear all,
I am trying to fit a powerlaw to a small dataset using
Scientific.Functions.LeastSquares fit.
Unfortunately, the algorithm seems to diverge and throws an
OverflowException.
Here is how I try it:
>>> from Scientific.Functions.LeastSquares import leastSquaresFit
>>>
>>> data = [
... (2
