error estimation in a non-linear least squares fitting
Robert Kern
robert.kern at gmail.com
Wed Oct 22 14:40:54 EDT 2008
Evelien wrote:
> Thanks Robert for your reply. I must say I am kind of disappointed if
> that is the only solution. I thought that such a standard problem as
> least squares fitting, would always give you an estimation of the
> error bars, without having to look up how you can convert a covariance
> matrix into error bars...
If you want an all-singing, all-dancing statistics-oriented nonlinear
least-squares interface, you can use scipy.odr. The numerical algorithm in
leastsq() outputs a covariance matrix naturally. Interpreting that to give you
statistical error bars requires some care and judgment. scipy.optimize is not a
statistical package.
--
Robert Kern
"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it as though it had
an underlying truth."
-- Umberto Eco
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