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• E04 Introduction
• e04ab – Minimum, function of one variable using function values only
• e04bb – Minimum, function of one variable, using first derivative
• e04cc – Unconstrained minimum, simplex algorithm, function of several variables using function values only (comprehensive)
• e04dg – Unconstrained minimum, preconditioned conjugate gradient algorithm, function of several variables using first derivatives (comprehensive)
• e04dk – Supply optional parameter values to e04dg
• e04fc – Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using function values only (comprehensive)
• e04fy – Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using function values only (easy-to-use)
• e04gb – Unconstrained minimum of a sum of squares, combined Gauss–Newton and quasi-Newton algorithm using first derivatives (comprehensive)
• e04gd – Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using first derivatives (comprehensive)
• e04gy – Unconstrained minimum of a sum of squares, combined Gauss–Newton and quasi-Newton algorithm, using first derivatives (easy-to-use)
• e04gz – Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using first derivatives (easy-to-use)
• e04hc – Check user's routine for calculating first derivatives of function
• e04hd – Check user's routine for calculating second derivatives of function
• e04he – Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm, using second derivatives (comprehensive)
• e04hy – Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm, using second derivatives (easy-to-use)
• e04jy – Minimum, function of several variables, quasi-Newton algorithm, simple bounds, using function values only (easy-to-use)
• e04kd – Minimum, function of several variables, modified Newton algorithm, simple bounds, using first derivatives (comprehensive)
• e04ky – Minimum, function of several variables, quasi-Newton algorithm, simple bounds, using first derivatives (easy-to-use)
• e04kz – Minimum, function of several variables, modified Newton algorithm, simple bounds, using first derivatives (easy-to-use)
• e04lb – Minimum, function of several variables, modified Newton algorithm, simple bounds, using first and second derivatives (comprehensive)
• e04ly – Minimum, function of several variables, modified Newton algorithm, simple bounds, using first and second derivatives (easy-to-use)
• e04mf – LP problem (dense)
• e04mh – Supply optional parameter values to e04mf
• e04nc – Convex QP problem or linearly-constrained linear least-squares problem (dense)
• e04ne – Supply optional parameter values to e04nc
• e04nf – QP problem (dense)
• e04nh – Supply optional parameter values to e04nf
• e04nk – LP or QP problem (sparse)
• e04nm – Supply optional parameter values to e04nk
• e04np – Initialization routine for e04nq
• e04nq – LP or QP problem (suitable for sparse problems)
• e04ns – Set a single option for e04nq from a character string
• e04nt – Set a single option for e04nq from an integer argument
• e04nu – Set a single option for e04nq from a real argument
• e04nx – Get the setting of an integer valued option of e04nq
• e04ny – Get the setting of a real valued option of e04nq
• e04uc – Minimum, function of several variables, sequential QP method, nonlinear constraints, using function values and optionally first derivatives (forward communication, comprehensive)
• e04ue – Supply optional parameter values to e04uc or e04uf
• e04uf – Minimum, function of several variables, sequential QP method, nonlinear constraints, using function values and optionally first derivatives (reverse communication, comprehensive)
• e04ug – NLP problem (sparse)
• e04uj – Supply optional parameter values to e04ug
• e04un – Minimum of a sum of squares, nonlinear constraints, sequential QP method, using function values and optionally first derivatives (comprehensive)
• e04ur – Supply optional parameter values to e04us
• e04us – Minimum of a sum of squares, nonlinear constraints, sequential QP method, using function values and optionally first derivatives (comprehensive)
• e04vg – Initialization routine for e04vh
• e04vh – General sparse nonlinear optimizer
• e04vj – Determine the pattern of nonzeros in the Jacobian matrix for e04vh
• e04vl – Set a single option for e04vh from a character string
• e04vm – Set a single option for e04vh from an integer argument
• e04vn – Set a single option for e04vh from a real argument
• e04vr – Get the setting of an integer valued option of e04vh
• e04vs – Get the setting of a real valued option of e04vh
• e04wb – Initialization routine for e04dg e04mf e04nc e04nf e04uf e04ug e04us
• e04wc – Initialization routine for e04wd
• e04wd – Solves the nonlinear programming (NP) problem
• e04wf – Set a single option for e04wd from a character string
• e04wg – Set a single option for e04wd from an integer argument
• e04wh – Set a single option for e04wd from a real argument
• e04wk – Get the setting of an integer valued option of e04wd
• e04wl – Get the setting of a real valued option of e04wd
• e04xa – Estimate (using numerical differentiation) gradient and/or Hessian of a function
• e04ya – Check user's routine for calculating Jacobian of first derivatives
• e04yb – Check user's routine for calculating Hessian of a sum of squares
• e04yc – Covariance matrix for nonlinear least-squares problem (unconstrained)
• e04zc – Check user's routines for calculating first derivatives of function and constraints