[SciPy-User] robust fit

[josef.pktd at gmail.com]

On Tue, May 31, 2011 at 10:17 AM, Sturla Molden <sturla at molden.no> wrote:
> Den 30.05.2011 13:19, skrev Matthieu Brucher:
>>
>> It seems to me that least squares cannot lead to a ribust fit in the
>> usual sense.
>
> Leastsq is actually Levenberg-Marquardt (lmder and lmdif from MINPACK).
> It can
> be used to minimize any cost function if you provide the Jacobian.

Do you have an example for this?
>From the docstring of lmdif and lmder it can only minimize sum of squares, e.g.

c     the purpose of lmdif is to minimize the sum of the squares of
c     m nonlinear functions in n variables by a modification of
c     the levenberg-marquardt algorithm.

Josef

>
> Sturla
> _______________________________________________
> SciPy-User mailing list
> SciPy-User at scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>