Andrew Clausen wrote:
I've been working on improving R's optim() command, which does general purpose
unconstrained optimization. Obviously, this is important for many statistics
computations, such as maximum likelihood, method of moments, etc. I have
focused my efforts of the BFGS method, mainly because it best matches my
current projects.
Hi, I came across this posting from a couple of years ago. If you are
still working on this, you might be interested in my free-software
(LGPL) library NLopt, which provides a single API for a large number of
nonlinear-optimization routines:
http://ab-initio.mit.edu/nlopt
It includes:
* Unconstrained optimization, bound constraints, and general nonlinear
inequality constraints
* Global and local optimization
* Optimization using function values only and optimization that
exploits gradient information if it is available.
Currently, it is callable from C, Fortran, Matlab, and GNU Octave, but
it would be great to have a GNU R interface as well.
Regards,
Steven G. Johnson
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