MINIMIZERS: Octave functions for minimization

Ben Sapp ()
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Ben Sapp: Los Alamos National Laboratory

Octave codes

Abstract: deriv.m -> numerically calculates 1st,2nd,3rd or 4th derivatives of O(2) or O(4) of a scalar function. gradient.m -> numerically calculates the gradient of a multi-variable function. nrm.m -> Newton-Raphson minimization of a scalar function. gs.m -> Golden Section search for a minimum of a scalar function. __quasi_func__.m -> Used internally by bfgs and dfp. This turns the multi-variable functions you supply bfgs and dfp into a scalar function along some line determined by the bfgs and dfp algorithm. Then this scalar function is minimized with nrm.m. dfp.m -> Davidon-Fletcher-Powell minimization of a multi-variable function. bfgs.m -> Broyden and company minimization of a multi-variable function. dfp and bfgs both need some improvement. They never re-calculate the inverse hessian. This makes them somewhat slow when the hessian changes drastically. I will eventually have them do this. They also do not check the arguements supplied for sanity.

Language: Octave
Requires: Octave
Date: 2000-04-19
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Persistent link: https://EconPapers.repec.org/RePEc:cod:octave:c042506

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