NAG C Library Manual, Mark 7 : e04 Chapter Contents

e04 – Minimizing or Maximizing a Function

Routine Name	Mark of Introduction	Purpose
e04abc Example Text	5	nag_opt_one_var_no_deriv Minimizes a function of one variable, using function values only
e04bbc Example Text	5	nag_opt_one_var_deriv Minimizes a function of one variable, requires first derivatives
e04ccc Example Text Example Data	4	nag_opt_simplex Unconstrained minimization using simplex algorithm
e04dgc Example Text Example Data	2	nag_opt_conj_grad Unconstrained minimization using conjugate gradients
e04fcc Example Text Example Data	2	nag_opt_lsq_no_deriv Unconstrained nonlinear least squares (no derivatives required)
e04gbc Example Text Example Data	2	nag_opt_lsq_deriv Unconstrained nonlinear least squares (first derivatives required)
e04hcc Example Text	2	nag_opt_check_deriv Derivative checker for use with e04kbc
e04hdc Example Text	5	nag_opt_check_2nd_deriv Checks second derivatives of a user-defined function
e04jbc Example Text Example Data	2	nag_opt_bounds_no_deriv Bound constrained nonlinear minimization (no derivatives required)
e04kbc Example Text Example Data	2	nag_opt_bounds_deriv Bound constrained nonlinear minimization (first derivatives required)
e04lbc Example Text Example Data	5	nag_opt_bounds_2nd_deriv Solves bound constrained problems (first and second derivatives required)
e04mfc Example Text Example Data	2	nag_opt_lp Linear programming
e04myc	5	nag_opt_sparse_mps_free Free memory allocated by e04mzc
e04mzc Example Text Example Data	5	nag_opt_sparse_mps_read Read MPSX data for sparse LP or QP problem from a file
e04ncc Example Text Example Data	5	nag_opt_lin_lsq Solves linear least-squares and convex quadratic programming problems (non-sparse)
e04nfc Example Text Example Data	2	nag_opt_qp Quadratic programming
e04nkc Example Text Example Data	5	nag_opt_sparse_convex_qp Solves sparse linear programming or convex quadratic programming problems
e04ucc Example Text Example Data	4	nag_opt_nlp Minimization with nonlinear constraints using a sequential QP method
e04ugc Example Text Example Data	6	nag_opt_nlp_sparse NLP problem (sparse)
e04unc Example Text Example Data	5	nag_opt_nlin_lsq Solves nonlinear least-squares problems using the sequential QP method
e04xac Example Text	5	nag_opt_estimate_deriv Computes an approximation to the gradient vector and/or the Hessian matrix for use with e04ucc and other nonlinear optimization functions
e04xxc	2	nag_opt_init Initialisation function for option setting
e04xyc	2	nag_opt_read Read options from a text file
e04xzc	2	nag_opt_free Memory freeing function for use with option setting
e04yac Example Text Example Data	2	nag_opt_lsq_check_deriv Least-squares derivative checker for use with e04gbc
e04ycc Example Text Example Data	2	nag_opt_lsq_covariance Covariance matrix for nonlinear least-squares

Chapter Introduction

NAG C Library Manual