[SciPy-user] nonlinear fit with non uniform error?
Wed Jun 20 08:09:41 CDT 2007
We have a set of data that we fit to a nonlinear function using
scipy.optimize.leastsq that, AFAIK, uses the Levenberg-Marquardt method.
Talking with a collegue of another lab, he pointed me that the dataset
we fit usually has intrinsically more noise in the first part of the
data than the latter. So he fitted by taking into account the non
uniform error -that is, instead of using plain chi-square, giving more
weight to the distance from points with less intrinsic error. He told me
that on Origin there is a function that does it. Is there something
similar on scipy?
University of Bologna
Department of Biochemistry "G.Moruzzi"
Via Irnerio 48, 40126 Bologna, Italy
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