Interfaces to routines from the NAG Fortran library


Documentation for package ‘NAGFWrappers’ version 23.0

Help Pages

a00ad a00ad: Library identification, details of implementation, major and minor marks
e04ab e04ab: Minimum, function of one variable using function values only
e04bb e04bb: Minimum, function of one variable, using first derivative
e04cb e04cb: Unconstrained minimization using simplex algorithm, function of several variables using function values only
e04dg e04dg: Unconstrained minimum, preconditioned conjugate gradient algorithm, function of several variables using first derivatives (comprehensive)
e04fc e04fc: Unconstrained minimum of a sum of squares, combined Gauss-Newton and modified Newton algorithm using function values only (comprehensive)
e04fy e04fy: Unconstrained minimum of a sum of squares, combined Gauss-Newton and modified Newton algorithm using function values only (easy-to-use)
e04gd e04gd: Unconstrained minimum of a sum of squares, combined Gauss-Newton and modified Newton algorithm using first derivatives (comprehensive)
e04gy e04gy: Unconstrained minimum of a sum of squares, combined Gauss-Newton and quasi-Newton algorithm, using first derivatives (easy-to-use)
e04gz e04gz: Unconstrained minimum of a sum of squares, combined Gauss-Newton and modified Newton algorithm using first derivatives (easy-to-use)
e04hc e04hc: Check user's function for calculating first derivatives of function
e04hd e04hd: Check user's function for calculating second derivatives of function
e04he e04he: Unconstrained minimum of a sum of squares, combined Gauss-Newton and modified Newton algorithm, using second derivatives (comprehensive)
e04hy e04hy: Unconstrained minimum of a sum of squares, combined Gauss-Newton and modified Newton algorithm, using second derivatives (easy-to-use)
e04jc e04jc: Minimum by quadratic approximation, function of several variables, simple bounds, using function values only
e04jy e04jy: Minimum, function of several variables, quasi-Newton algorithm, simple bounds, using function values only (easy-to-use)
e04kd e04kd: Minimum, function of several variables, modified Newton algorithm, simple bounds, using first derivatives (comprehensive)
e04ky e04ky: Minimum, function of several variables, quasi-Newton algorithm, simple bounds, using first derivatives (easy-to-use)
e04kz e04kz: Minimum, function of several variables, modified Newton algorithm, simple bounds, using first derivatives (easy-to-use)
e04lb e04lb: Minimum, function of several variables, modified Newton algorithm, simple bounds, using first and second derivatives (comprehensive)
e04ly e04ly: Minimum, function of several variables, modified Newton algorithm, simple bounds, using first and second derivatives (easy-to-use)
e04mf e04mf: LP problem (dense)
e04nc e04nc: Convex QP problem or linearly-constrained linear least squares problem (dense)
e04nf e04nf: QP problem (dense)
e04nk e04nk: LP or QP problem (sparse)
e04nq e04nq: LP or QP problem (suitable for sparse problems)
e04uc e04uc: Minimum, function of several variables, sequential QP method, nonlinear constraints, using function values and optionally first derivatives (comprehensive)
e04uf e04uf: Minimum, function of several variables, sequential QP method, nonlinear constraints, using function values and optionally first derivatives (reverse communication, comprehensive)
e04ug e04ug: NLP problem (sparse)
e04us e04us: Minimum of a sum of squares, nonlinear constraints, sequential QP method, using function values and optionally first derivatives (comprehensive)
e04vj e04vj: Determine the pattern of nonzeros in the Jacobian matrix for e04vh
e04wd e04wd: Solves the nonlinear programming (NP) problem
e04xa e04xa: Estimate (using numerical differentiation) gradient and/or Hessian of a function
e04ya e04ya: Check user's function for calculating Jacobian of first derivatives
e04yb e04yb: Check user's function for calculating Hessian of a sum of squares
e04yc e04yc: Covariance matrix for nonlinear least squares problem (unconstrained)
e05jb e05jb: Global optimization by multi-level coordinate search, simple bounds, using function values only
f08fa f08fa: Computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix
g02aa g02aa: Computes the nearest correlation matrix to a real square matrix, using the method of Qi and Sun
g02ab g02ab: Computes the nearest correlation matrix to a real square matrix, augmented g02aa to incorporate weights and bounds
g02ae g02ae: Computes the nearest correlation matrix with k-factor structure to a real square matrix
NAGFWrappers Provides interfaces to NAG Fortran Library
s17dc s17dc: Bessel functions Y_nu + a(z), real a >= 0, complex z, nu = 0 , 1 , 2 , . . .
s17de s17de: Bessel functions J_nu + a(z), real a >= 0, complex z, nu = 0 , 1 , 2 , . . .
s17dg s17dg: Airy functions Ai(z) and Ai'(z), complex z
s17dh s17dh: Airy functions Bi(z) and Bi'(z), complex z
s17dl s17dl: Hankel functions H_nu + a^(j)(z), j = 1 , 2, real a >= 0, complex z, nu=0 , 1 , 2 , . . .
s18dc s18dc: Modified Bessel functions K_nu + a(z), real a >= 0, complex z, nu = 0 , 1 , 2 , . . .
s18de s18de: Modified Bessel functions I_nu + a(z), real a >= 0, complex z, nu = 0 , 1 , 2 , . . .
s18gk s18gk: Bessel function of the 1st kind J_alpha +/- n(z)
s22aa s22aa: Legendre functions of 1st kind P_n^m(x) or overlineP_n^m(x)
x02aj x02aj: The machine precision
x02al x02al: The largest positive model number