Uses of Interface
optimization.Uncmin_methods

Packages that use Uncmin_methods

optimization

Uses of Uncmin_methods in optimization

Classes in optimization that implement Uncmin_methods

class

UncminTest_f77 This class tests the Uncmin_f77 class.

Methods in optimization with parameters of type Uncmin_methods

static void	Uncmin_f77.dogdrv_f77(int n, double[] x, double[] f, double[] g, double[][] a, double[] p, double[] xpls, double[] fpls, Uncmin_methods minclass, double[] sx, double[] stepmx, double[] steptl, double[] dlt, int[] iretcd, boolean[] mxtake, double[] sc, double[] wrk1, double[] wrk2, double[] wrk3) The dogdrv_f77 method finds the next Newton iterate (xpls) by the double dogleg method.
static void	Uncmin_f77.fstocd_f77(int n, double[] x, Uncmin_methods minclass, double[] sx, double rnoise, double[] g) The fstocd_f77 method finds a central difference approximation to the gradient of the function to be minimized.
static void	Uncmin_f77.fstofd_f77(int n, double[] xpls, Uncmin_methods minclass, double[] fpls, double[][] a, double[] sx, double rnoise, double[] fhat) This version of the fstofd_f77 method finds a finite difference approximation to the Hessian.
static void	Uncmin_f77.fstofd_f77(int n, double[] xpls, Uncmin_methods minclass, double[] fpls, double[] g, double[] sx, double rnoise) This version of the fstofd_f77 method finds first order finite difference approximations for gradients.
static void	Uncmin_f77.grdchk_f77(int n, double[] x, Uncmin_methods minclass, double[] f, double[] g, double[] typsiz, double[] sx, double[] fscale, double rnf, double analtl, double[] gest) The grdchk_f77 method checks the analytic gradient supplied by the user.
static void	Uncmin_f77.heschk_f77(int n, double[] x, Uncmin_methods minclass, double[] f, double[] g, double[][] a, double[] typsiz, double[] sx, double rnf, double analtl, int[] iagflg, double[] udiag, double[] wrk1, double[] wrk2) The heschk_f77 method checks the analytic Hessian supplied by the user.
static void	Uncmin_f77.hookdr_f77(int n, double[] x, double[] f, double[] g, double[][] a, double[] udiag, double[] p, double[] xpls, double[] fpls, Uncmin_methods minclass, double[] sx, double[] stepmx, double[] steptl, double[] dlt, int[] iretcd, boolean[] mxtake, double[] amu, double[] dltp, double[] phi, double[] phip0, double[] sc, double[] xplsp, double[] wrk0, double epsm, int[] itncnt) The hookdr_f77 method finds a next Newton iterate (xpls) by the More-Hebdon technique.
static void	Uncmin_f77.lnsrch_f77(int n, double[] x, double[] f, double[] g, double[] p, double[] xpls, double[] fpls, Uncmin_methods minclass, boolean[] mxtake, int[] iretcd, double[] stepmx, double[] steptl, double[] sx) The lnsrch_f77 method finds a next Newton iterate by line search.
static void	Uncmin_f77.optdrv_f77(int n, double[] x, Uncmin_methods minclass, double[] typsiz, double[] fscale, int[] method, int[] iexp, int[] msg, int[] ndigit, int[] itnlim, int[] iagflg, int[] iahflg, double[] dlt, double[] gradtl, double[] stepmx, double[] steptl, double[] xpls, double[] fpls, double[] gpls, int[] itrmcd, double[][] a, double[] udiag, double[] g, double[] p, double[] sx, double[] wrk0, double[] wrk1, double[] wrk2, double[] wrk3) The optdrv_f77 method is the driver for the nonlinear optimization problem.
static void	Uncmin_f77.optif0_f77(int n, double[] x, Uncmin_methods minclass, double[] xpls, double[] fpls, double[] gpls, int[] itrmcd, double[][] a, double[] udiag) The optif0_f77 method minimizes a smooth nonlinear function of n variables.
static void	Uncmin_f77.optif9_f77(int n, double[] x, Uncmin_methods minclass, double[] typsiz, double[] fscale, int[] method, int[] iexp, int[] msg, int[] ndigit, int[] itnlim, int[] iagflg, int[] iahflg, double[] dlt, double[] gradtl, double[] stepmx, double[] steptl, double[] xpls, double[] fpls, double[] gpls, int[] itrmcd, double[][] a, double[] udiag) The optif9_f77 method minimizes a smooth nonlinear function of n variables.
static void	Uncmin_f77.sndofd_f77(int n, double[] xpls, Uncmin_methods minclass, double[] fpls, double[][] a, double[] sx, double rnoise, double[] stepsz, double[] anbr) The sndofd_f77 method finds second order forward finite difference approximations to the Hessian.
static void	Uncmin_f77.tregup_f77(int n, double[] x, double[] f, double[] g, double[][] a, Uncmin_methods minclass, double[] sc, double[] sx, boolean[] nwtake, double[] stepmx, double[] steptl, double[] dlt, int[] iretcd, double[] xplsp, double[] fplsp, double[] xpls, double[] fpls, boolean[] mxtake, int method, double[] udiag) The tregup_f77 method decides whether to accept xpls = x + sc as the next iterate and update the trust region dlt.