Hi Everyone, I was wondering if you could help me. I have a nonlinear least squares problem that has a large number of parameters, greater than 1,000. I am currently solving it using the current version of GSL, Levenberg-Marquardt algorithm. This works well but it is slow and takes several seconds. I would ideally like it to be a lot less time, and have read that I can exploit the spareness of the jacobians using QR factorization. Most of my parameters are not dependent on other parameters and my jacobian is therefore quite sparse.
I was wondering if anyone knows the answers to my follwing questions: 1) How to exploit the sparseness of Jacobians in Levenberg-Marquardt using QR. 2) How to exploit the sparseness of Jacobians in Levenberg-Marquardt alternative ways. 3) If it is possible to do this in the current GSL. 4) If not currently possible, will the sparseness be exploited in GSL at a later date. 5) Other algorithms or libraries I could use. Thanks, Tom _________________________________________________________________ Save time by using Hotmail to access your other email accounts. http://clk.atdmt.com/UKM/go/167688463/direct/01/_______________________________________________ Help-gsl mailing list [email protected] http://lists.gnu.org/mailman/listinfo/help-gsl
