Hi... Not sure if this is the right forum for this but here goes...
I am doing multi-dimensional minimization via conjugate gradients. According to the GSL reference manual, these algorithms proceed by successive line minimizations. Once it has converged along a given direction, it chooses a new direction in which to search. My question is: what method is used for the line minimization? Does the user have any control over this? From the example at http://www.gnu.org/software/gsl/manual/html_node/Multimin-Examples.html it looks like there is simply a step size that increases as we move downhill... eventually we overshoot the minimum, and then it backtracks. Is this right? I'm not sure why one would do this instead of some kind of Brent method or something based on parabolas. Nor is it clear to me what it does during the backtracking step. And when there is a change of direction, what step size is used for the first step along that direction? I have in mind a function with many minima and I am interested in how the minimum that is found depends on the starting point used. I guess this depends on the implementation, so it would be useful if a few more details of the minimization algorithm were available somewhere. Sorry if this is addressed somewhere and I missed it -- thanks for any help Rob _______________________________________________ Help-gsl mailing list [email protected] http://lists.gnu.org/mailman/listinfo/help-gsl
