ADMB Documentation
11.1.2497

Functions  
void  fmm::fmin (const double &f, const dvector &x, const dvector &g) 
Function fmin contains QuasiNewton function minimizer with inexact line search using Wolfe conditions and BFGS correction formula for Hessian update. 
Function fmin contains QuasiNewton function minimizer with inexact line search using Wolfe conditions and BFGS correction formula for Hessian update.
The algorithm consists of the following steps (in the order of execution):
Convergence is detected if the maximal gradient component falls below small constant (see label20)
Requires:
_f  Value of function to be minimized. 
_x  Vector of independent variables. 
_g  Vector containing the partial derivatives of _f with respect to each independent variable. The gradient vector returned by gradcalc. Pre: Some class member variables can be initialized by user prior to calling this function. These control variables may change the behavior of fmin, they are: maxfn (maximal number of function evaluations, after which minimization stops) crit (convergence criterion constant) imax (maximal number of function evaluations within one linear search* before to stop) iprint (flag to allow (=1) or supress (=0) printing intermediate statistics min_improve (stop after 10 iterations with overall function decrease less than this value) The default values can be found in function set_defaults of class fmm_control Modifies: The Hessian matrix (and not its inverse) h Returns (via parameter vector x): A vector x after a step of linear search in the direction of gradient descent 
Definition at line 215 of file newfmin.cpp.
Referenced by fmm::minimize(), function_minimizer::prof_minimize(), function_minimizer::prof_minimize_re(), and function_minimizer::quasi_newton_block().
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