[SciPy-Dev] Levenberg-Marquardt Implementation

[Sturla Molden]

scipy.optimize.leastsq uses a trust-region Levenberg-Marquardt solver from
MINPACK.

I think one that uses LAPACK subroutine DGELS could be made more efficient.
MINPACK has an unoptimized QR factorization and is also not re-entrant
(global variables). But the numerical quality and stability of the MINPACK
version in undisputed.

Sturla



Nico Del Piano <ndel314 at gmail.com> wrote:
> Hi all,
> 
> I am Nicolas Del Piano, and currently studying the last year of computer
> science career. I was searching for a GSoC project that involves
> mathematical concepts, and I found one very interesting. I have
> experience on python programming and I studied calculus, so I have a
> background of the problem context.
> 
> I am interested on the implementation and testing of Levenberg-Marquardt
> / trust region nonlinear least squares algorithm.
> 
> Here are some useful links, that I have searched to having a reference about the problem:
> 
> <a
> href="http://ananth.in/docs/lmtut.pdf">http://ananth.in/docs/lmtut.pdf</a> (Introduction)
> www.cs.nyu.edu/~roweis/notes/lm.pdf (Optimization) <a
> href="http://scribblethink.org/Computer/Javanumeric/index.html">http://scribblethink.org/Computer/Javanumeric/index.html</a>
> (java implementation)
> 
> I would be glad if there is an interested mentor to discuss the issues,
> talk about the problem and its possible implementations, and provide me
> some support and guide.
> 
> Thanks!
> 
> Regards.
> 
> _______________________________________________ SciPy-Dev mailing list
> SciPy-Dev at scipy.org <a
> href="http://mail.scipy.org/mailman/listinfo/scipy-dev">http://mail.scipy.org/mailman/listinfo/scipy-dev</a>