Category Documents
NAG/e04ncc
Solves linear least-squares and convex quadratic programming problems (non-sparse)
NAG/e04ucc
Minimization with nonlinear constraints using a sequential QP method
NAG/e04dgc
Unconstrained minimization using conjugate gradients
NAG/e04fcc
Unconstrained nonlinear least-squares (no derivatives required)
NAG/e04gbc
Unconstrained nonlinear least-squares (first derivatives required)
NAG/e04jbc
Bound constrained nonlinear minimization (no derivatives required)
NAG/e04kbc
Bound constrained nonlinear minimization (first derivatives required)
NAG/e04nkc
Solves sparse linear programming or convex quadratic programming problems
NAG/e04unc
Solves nonlinear least-squares problems using the sequential QP method
NAG/e04lbc
Solves bound constrained problems (first and second derivatives required)
NAG/e04hdc
Checks second derivatives of a user-defined function
NAG/e04yac
Least-squares derivative checker for use with e04gbc (nag_opt_lsq_deriv)
NAG/e04ycc
Covariance matrix for nonlinear least-squares
NAG/e04xac
Computes an approximation to the gradient vector and/or the Hessian matrix
NAG/e04bbc
Minimizes a function of one variable, requires first derivatives
NAG/e04abc
Minimizes a function of one variable, using function values only
NAG/e04ccc
Unconstrained minimization using simplex algorithm
NAG/e04mzc
Read MPSX data for sparse LP or QP problem from a file
NAG/e04
Minimizing or Maximizing a Function