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MINIMIZERS: Octave functions for minimization

Author

Listed:
  • Ben Sapp

    (Los Alamos National Laboratory)

Programming Language

Octave

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.

Suggested Citation

  • Ben Sapp, 2000. "MINIMIZERS: Octave functions for minimization," Octave codes C042506, .
    • Handle: RePEc:cod:octave:c042506
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    Keywords

    Octave;

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