|
Mark 20 Library Contents
A00: Library Identification
A00AAF |
Prints details of the NAG Fortran Library implementation |
A02: Complex Arithmetic
C02: Zeros of Polynomials
C05: Roots of One or More Transcendental Equations
C06: Summation of Series
Chapter Introduction |
C06BAF
|
Acceleration of convergence of sequence, Shanks' transformation and epsilon algorithm
|
C06DBF
|
Sum of a Chebyshev series
|
C06EAF
|
Single one-dimensional real discrete Fourier transform, no extra workspace
|
C06EBF
|
Single one-dimensional Hermitian discrete Fourier transform, no extra workspace
|
C06ECF
|
Single one-dimensional complex discrete Fourier transform, no extra workspace
|
C06EKF
|
Circular convolution or correlation of two real vectors, no extra workspace
|
C06FAF
|
Single one-dimensional real discrete Fourier transform, extra workspace for greater speed
|
C06FBF
|
Single one-dimensional Hermitian discrete Fourier transform, extra workspace for greater speed
|
C06FCF
|
Single one-dimensional complex discrete Fourier transform, extra workspace for greater speed
|
C06FFF
|
One-dimensional complex discrete Fourier transform of multi-dimensional data
|
C06FJF
|
Multi-dimensional complex discrete Fourier transform of multi-dimensional data
|
C06FKF
|
Circular convolution or correlation of two real vectors, extra workspace for greater speed
|
C06FPF
|
Multiple one-dimensional real discrete Fourier transforms |
C06FQF
|
Multiple one-dimensional Hermitian discrete Fourier transforms |
C06FRF
|
Multiple one-dimensional complex discrete Fourier transforms |
C06FUF
|
Two-dimensional complex discrete Fourier transform |
C06FXF
|
Three-dimensional complex discrete Fourier transform |
C06GBF
|
Complex conjugate of Hermitian sequence |
C06GCF
|
Complex conjugate of complex sequence |
C06GQF
|
Complex conjugate of multiple Hermitian sequences |
C06GSF
|
Convert Hermitian sequences to general complex sequences |
C06HAF
|
Discrete sine transform |
C06HBF
|
Discrete cosine transform |
C06HCF
|
Discrete quarter-wave sine transform |
C06HDF
|
Discrete quarter-wave cosine transform |
C06LAF
|
Inverse Laplace transform, Crump's method
|
C06LBF
|
Inverse Laplace transform, modified Weeks' method
|
C06LCF
|
Evaluate inverse Laplace transform as computed by C06LBF |
C06PAF
|
Single one-dimensional real and Hermitian complex discrete Fourier transform, using complex data format for Hermitian sequences |
C06PCF
|
Single one-dimensional complex discrete Fourier transform, complex data format
|
C06PFF
|
One-dimensional complex discrete Fourier transform of multi-dimensional data (using complex data type)
|
C06PJF
|
Multi-dimensional complex discrete Fourier transform of multi-dimensional data (using complex data type)
|
C06PKF
|
Circular convolution or correlation of two complex vectors |
C06PPF
|
Multiple one-dimensional real and Hermitian complex discrete Fourier transforms, using complex data format for Hermitian sequences
|
C06PQF
|
Multiple one-dimensional real and Hermitian complex discrete Fourier transforms, using complex data format for Hermitian sequences
|
C06PRF
|
Multiple one-dimensional complex discrete Fourier transforms using complex data format
|
C06PSF
|
Multiple one-dimensional complex discrete Fourier transforms using complex data format and sequences stored as columns
|
C06PUF
|
Two-dimensional complex discrete Fourier transform, complex data format
|
C06PXF
|
Three-dimensional complex discrete Fourier transform, complex data format
|
C06RAF
|
Discrete sine transform (easy-to-use)
|
C06RBF
|
Discrete cosine transform (easy-to-use)
|
C06RCF
|
Discrete quarter-wave sine transform (easy-to-use)
|
C06RDF
|
Discrete quarter-wave cosine transform (easy-to-use)
|
D01: Quadrature
Chapter Introduction |
D01AHF
|
One-dimensional quadrature, adaptive, finite interval, strategy due to Patterson, suitable for well-behaved integrands
|
D01AJF
|
One-dimensional quadrature, adaptive, finite interval, strategy due to Piessens and de Doncker, allowing for badly-behaved integrands
|
D01AKF
|
One-dimensional quadrature, adaptive, finite interval, method suitable for oscillating functions
|
D01ALF
|
One-dimensional quadrature, adaptive, finite interval, allowing for singularities at user-specified break-points |
D01AMF
|
One-dimensional quadrature, adaptive, infinite or semi-infinite interval
|
D01ANF
|
One-dimensional quadrature, adaptive, finite interval, weight function cos(omega x) or sin(omega x) |
D01APF
|
One-dimensional quadrature, adaptive, finite interval, weight function with end-point singularities of algebraico-logarithmic type
|
D01AQF
|
One-dimensional quadrature, adaptive, finite interval, weight function 1/(x-c), Cauchy principal value (Hilbert transform)
|
D01ARF
|
One-dimensional quadrature, non-adaptive, finite interval with provision for indefinite integrals |
D01ASF
|
One-dimensional quadrature, adaptive, semi-infinite interval, weight function cos(omega x) or sin(omega x) |
D01ATF
|
One-dimensional quadrature, adaptive, finite interval, variant of D01AJF efficient on vector machines
|
D01AUF
|
One-dimensional quadrature, adaptive, finite interval, variant of D01AKF efficient on vector machines
|
D01BAF
|
One-dimensional Gaussian quadrature |
D01BBF
|
Pre-computed weights and abscissae for Gaussian quadrature rules, restricted choice of rule
|
D01BCF
|
Calculation of weights and abscissae for Gaussian quadrature rules, general choice of rule
|
D01BDF
|
One-dimensional quadrature, non-adaptive, finite interval
|
D01DAF
|
Two-dimensional quadrature, finite region
|
D01EAF
|
Multi-dimensional adaptive quadrature over hyper-rectangle, multiple integrands
|
D01FBF
|
Multi-dimensional Gaussian quadrature over hyper-rectangle |
D01FCF
|
Multi-dimensional adaptive quadrature over hyper-rectangle |
D01FDF
|
Multi-dimensional quadrature, Sag–Szekeres method, general product region or n-sphere |
D01GAF
|
One-dimensional quadrature, integration of function defined by data values, Gill–Miller method
|
D01GBF
|
Multi-dimensional quadrature over hyper-rectangle, Monte Carlo method
|
D01GCF
|
Multi-dimensional quadrature, general product region, number-theoretic method
|
D01GDF
|
Multi-dimensional quadrature, general product region, number-theoretic method, variant of D01GCF efficient on vector machines
|
D01GYF
|
Korobov optimal coefficients for use in D01GCF or D01GDF, when number of points is prime |
D01GZF
|
Korobov optimal coefficients for use in D01GCF or D01GDF, when number of points is product of two primes |
D01JAF
|
Multi-dimensional quadrature over an n-sphere, allowing for badly-behaved integrands
|
D01PAF
|
Multi-dimensional quadrature over an n-simplex |
D02: Ordinary Differential Equations
Chapter Introduction |
D02AGF
|
ODEs, boundary value problem, shooting and matching technique, allowing interior matching point, general parameters to be determined
|
D02BGF
|
ODEs, IVP, Runge–Kutta–Merson method, until a component attains given value (simple driver)
|
D02BHF
|
ODEs, IVP, Runge–Kutta–Merson method, until function of solution is zero (simple driver)
|
D02BJF
|
ODEs, IVP, Runge–Kutta method, until function of solution is zero, integration over range with intermediate output (simple driver)
|
D02CJF
|
ODEs, IVP, Adams method, until function of solution is zero, intermediate output (simple driver)
|
D02EJF
|
ODEs, stiff IVP, BDF method, until function of solution is zero, intermediate output (simple driver)
|
D02GAF
|
ODEs, boundary value problem, finite difference technique with deferred correction, simple nonlinear problem
|
D02GBF
|
ODEs, boundary value problem, finite difference technique with deferred correction, general linear problem
|
D02HAF
|
ODEs, boundary value problem, shooting and matching, boundary values to be determined
|
D02HBF
|
ODEs, boundary value problem, shooting and matching, general parameters to be determined
|
D02JAF
|
ODEs, boundary value problem, collocation and least-squares, single nth-order linear equation
|
D02JBF
|
ODEs, boundary value problem, collocation and least-squares, system of first-order linear equations
|
D02KAF
|
Second-order Sturm–Liouville problem, regular system, finite range, eigenvalue only
|
D02KDF
|
Second-order Sturm–Liouville problem, regular/singular system, finite/infinite range, eigenvalue only, user-specified break-points |
D02KEF
|
Second-order Sturm–Liouville problem, regular/singular system, finite/infinite range, eigenvalue and eigenfunction, user-specified break-points |
D02LAF
|
Second-order ODEs, IVP, Runge–Kutta–Nystrom method
|
D02LXF
|
Second-order ODEs, IVP, setup for D02LAF |
D02LYF
|
Second-order ODEs, IVP, diagnostics for D02LAF |
D02LZF
|
Second-order ODEs, IVP, interpolation for D02LAF |
D02M/N Introduction |
D02MVF
|
ODEs, IVP, DASSL method, setup for D02M–N routines
|
D02MZF
|
ODEs, IVP, interpolation for D02M–N routines, natural interpolant |
D02NBF
|
Explicit ODEs, stiff IVP, full Jacobian (comprehensive)
|
D02NCF
|
Explicit ODEs, stiff IVP, banded Jacobian (comprehensive)
|
D02NDF
|
Explicit ODEs, stiff IVP, sparse Jacobian (comprehensive)
|
D02NGF
|
Implicit/algebraic ODEs, stiff IVP, full Jacobian (comprehensive)
|
D02NHF
|
Implicit/algebraic ODEs, stiff IVP, banded Jacobian (comprehensive)
|
D02NJF
|
Implicit/algebraic ODEs, stiff IVP, sparse Jacobian (comprehensive)
|
D02NMF
|
Explicit ODEs, stiff IVP (reverse communication, comprehensive)
|
D02NNF
|
Implicit/algebraic ODEs, stiff IVP (reverse communication, comprehensive)
|
D02NRF
|
ODEs, IVP, for use with D02M–N routines, sparse Jacobian, enquiry routine
|
D02NSF
|
ODEs, IVP, for use with D02M–N routines, full Jacobian, linear algebra set up
|
D02NTF
|
ODEs, IVP, for use with D02M–N routines, banded Jacobian, linear algebra set up
|
D02NUF
|
ODEs, IVP, for use with D02M–N routines, sparse Jacobian, linear algebra set up
|
D02NVF
|
ODEs, IVP, BDF method, setup for D02M–N routines
|
D02NWF
|
ODEs, IVP, Blend method, setup for D02M–N routines
|
D02NXF
|
ODEs, IVP, sparse Jacobian, linear algebra diagnostics, for use with D02M–N routines
|
D02NYF
|
ODEs, IVP, integrator diagnostics, for use with D02M–N routines
|
D02NZF
|
ODEs, IVP, setup for continuation calls to integrator, for use with D02M–N routines
|
D02PCF
|
ODEs, IVP, Runge–Kutta method, integration over range with output
|
D02PDF
|
ODEs, IVP, Runge–Kutta method, integration over one step
|
D02PVF
|
ODEs, IVP, setup for D02PCF and D02PDF |
D02PWF
|
ODEs, IVP, resets end of range for D02PDF |
D02PXF
|
ODEs, IVP, interpolation for D02PDF |
D02PYF
|
ODEs, IVP, integration diagnostics for D02PCF and D02PDF |
D02PZF
|
ODEs, IVP, error assessment diagnostics for D02PCF and D02PDF |
D02QFF
|
ODEs, IVP, Adams method with root-finding (forward communication, comprehensive)
|
D02QGF
|
ODEs, IVP, Adams method with root-finding (reverse communication, comprehensive)
|
D02QWF
|
ODEs, IVP, setup for D02QFF and D02QGF |
D02QXF
|
ODEs, IVP, diagnostics for D02QFF and D02QGF |
D02QYF
|
ODEs, IVP, root-finding diagnostics for D02QFF and D02QGF |
D02QZF
|
ODEs, IVP, interpolation for D02QFF or D02QGF |
D02RAF
|
ODEs, general nonlinear boundary value problem, finite difference technique with deferred correction, continuation facility
|
D02SAF
|
ODEs, boundary value problem, shooting and matching technique, subject to extra algebraic equations, general parameters to be determined
|
D02TGF
|
nth-order linear ODEs, boundary value problem, collocation and least-squares |
D02TKF
|
ODEs, general nonlinear boundary value problem, collocation technique
|
D02TVF
|
ODEs, general nonlinear boundary value problem, setup for D02TKF |
D02TXF
|
ODEs, general nonlinear boundary value problem, continuation facility for D02TKF |
D02TYF
|
ODEs, general nonlinear boundary value problem, interpolation for D02TKF |
D02TZF
|
ODEs, general nonlinear boundary value problem, diagnostics for D02TKF |
D02XJF
|
ODEs, IVP, interpolation for D02M–N routines, natural interpolant |
D02XKF
|
ODEs, IVP, interpolation for D02M–N routines, C1 interpolant |
D02ZAF
|
ODEs, IVP, weighted norm of local error estimate for D02M–N routines
|
D03: Partial Differential Equations
Chapter Introduction |
D03EAF
|
Elliptic PDE, Laplace's equation, two-dimensional arbitrary domain
|
D03EBF
|
Elliptic PDE, solution of finite difference equations by SIP, five-point two-dimensional molecule, iterate to convergence
|
D03ECF
|
Elliptic PDE, solution of finite difference equations by SIP for seven-point three-dimensional molecule, iterate to convergence
|
D03EDF
|
Elliptic PDE, solution of finite difference equations by a multigrid technique
|
D03EEF
|
Discretize a second-order elliptic PDE on a rectangle |
D03FAF
|
Elliptic PDE, Helmholtz equation, three-dimensional Cartesian co-ordinates
|
D03MAF
|
Triangulation of plane region
|
D03NCF
|
Finite difference solution of the Black–Scholes equations |
D03NDF
|
Analytic solution of the Black–Scholes equations |
D03NEF
|
Compute average values for D03NDF |
D03PCF
|
General system of parabolic PDEs, method of lines, finite differences, one space variable
|
D03PDF
|
General system of parabolic PDEs, method of lines, Chebyshev C0 collocation, one space variable
|
D03PEF
|
General system of first-order PDEs, method of lines, Keller box discretisation, one space variable
|
D03PFF
|
General system of convection-diffusion PDEs with source terms in conservative form, method of lines, upwind scheme using numerical flux function based on Riemann solver, one space variable
|
D03PHF
|
General system of parabolic PDEs, coupled DAEs, method of lines, finite differences, one space variable
|
D03PJF
|
General system of parabolic PDEs, coupled DAEs, method of lines, Chebyshev C0 collocation, one space variable
|
D03PKF
|
General system of first-order PDEs, coupled DAEs, method of lines, Keller box discretisation, one space variable
|
D03PLF
|
General system of convection-diffusion PDEs with source terms in conservative form, coupled DAEs, method of lines, upwind scheme using numerical flux function based on Riemann solver, one space variable
|
D03PPF
|
General system of parabolic PDEs, coupled DAEs, method of lines, finite differences, remeshing, one space variable
|
D03PRF
|
General system of first-order PDEs, coupled DAEs, method of lines, Keller box discretisation, remeshing, one space variable
|
D03PSF
|
General system of convection-diffusion PDEs with source terms in conservative form, coupled DAEs, method of lines, upwind scheme using numerical flux function based on Riemann solver, remeshing, one space variable
|
D03PUF
|
Roe's approximate Riemann solver for Euler equations in conservative form, for use with D03PFF, D03PLF and D03PSF |
D03PVF
|
Osher's approximate Riemann solver for Euler equations in conservative form, for use with D03PFF, D03PLF and D03PSF |
D03PWF
|
Modified HLL Riemann solver for Euler equations in conservative form, for use with D03PFF, D03PLF and D03PSF |
D03PXF
|
Exact Riemann Solver for Euler equations in conservative form, for use with D03PFF, D03PLF and D03PSF |
D03PYF
|
PDEs, spatial interpolation with D03PDF or D03PJF |
D03PZF
|
PDEs, spatial interpolation with D03PCF, D03PEF, D03PFF, D03PHF, D03PKF, D03PLF, D03PPF, D03PRF or D03PSF |
D03RAF
|
General system of second-order PDEs, method of lines, finite differences, remeshing, two space variables, rectangular region
|
D03RBF
|
General system of second-order PDEs, method of lines, finite differences, remeshing, two space variables, rectilinear region
|
D03RYF
|
Check initial grid data in D03RBF |
D03RZF
|
Extract grid data from D03RBF |
D03UAF
|
Elliptic PDE, solution of finite difference equations by SIP, five-point two-dimensional molecule, one iteration |
D03UBF
|
Elliptic PDE, solution of finite difference equations by SIP, seven-point three-dimensional molecule, one iteration |
D04: Numerical Differentiation
D05: Integral Equations
D06: Mesh Generation
E01: Interpolation
Chapter Introduction |
E01AAF
|
Interpolated values, Aitken's technique, unequally spaced data, one variable
|
E01ABF
|
Interpolated values, Everett's formula, equally spaced data, one variable
|
E01AEF
|
Interpolating functions, polynomial interpolant, data may include derivative values, one variable
|
E01BAF
|
Interpolating functions, cubic spline interpolant, one variable
|
E01BEF
|
Interpolating functions, monotonicity-preserving, piecewise cubic Hermite, one variable
|
E01BFF
|
Interpolated values, interpolant computed by E01BEF, function only, one variable
|
E01BGF
|
Interpolated values, interpolant computed by E01BEF, function and first derivative, one variable
|
E01BHF
|
Interpolated values, interpolant computed by E01BEF, definite integral, one variable
|
E01DAF
|
Interpolating functions, fitting bicubic spline, data on rectangular grid
|
E01RAF
|
Interpolating functions, rational interpolant, one variable
|
E01RBF
|
Interpolated values, evaluate rational interpolant computed by E01RAF, one variable
|
E01SAF
|
Interpolating functions, method of Renka and Cline, two variables
|
E01SBF
|
Interpolated values, evaluate interpolant computed by E01SAF, two variables
|
E01SGF
|
Interpolating functions, modified Shepard's method, two variables
|
E01SHF
|
Interpolated values, evaluate interpolant computed by E01SGF, function and first derivatives, two variables
|
E01TGF
|
Interpolating functions, modified Shepard's method, three variables |
E01THF
|
Interpolated values, evaluate interpolant computed by E01TGF, function and first derivatives, three variables
|
E02: Curve and Surface Fitting
Chapter Introduction |
E02ACF
|
Minimax curve fit by polynomials |
E02ADF
|
Least-squares curve fit, by polynomials, arbitrary data points
|
E02AEF
|
Evaluation of fitted polynomial in one variable from Chebyshev series form (simplified parameter list)
|
E02AFF
|
Least-squares polynomial fit, special data points (including interpolation)
|
E02AGF
|
Least-squares polynomial fit, values and derivatives may be constrained, arbitrary data points
|
E02AHF
|
Derivative of fitted polynomial in Chebyshev series form
|
E02AJF
|
Integral of fitted polynomial in Chebyshev series form
|
E02AKF
|
Evaluation of fitted polynomial in one variable from Chebyshev series form
|
E02BAF
|
Least-squares curve cubic spline fit (including interpolation)
|
E02BBF
|
Evaluation of fitted cubic spline, function only
|
E02BCF
|
Evaluation of fitted cubic spline, function and derivatives |
E02BDF
|
Evaluation of fitted cubic spline, definite integral |
E02BEF
|
Least-squares cubic spline curve fit, automatic knot placement
|
E02CAF
|
Least-squares surface fit by polynomials, data on lines |
E02CBF
|
Evaluation of fitted polynomial in two variables
|
E02DAF
|
Least-squares surface fit, bicubic splines |
E02DCF
|
Least-squares surface fit by bicubic splines with automatic knot placement, data on rectangular grid
|
E02DDF
|
Least-squares surface fit by bicubic splines with automatic knot placement, scattered data
|
E02DEF
|
Evaluation of fitted bicubic spline at a vector of points
|
E02DFF
|
Evaluation of fitted bicubic spline at a mesh of points
|
E02GAF
|
L1-approximation by general linear function
|
E02GBF
|
L1-approximation by general linear function subject to linear inequality constraints |
E02GCF
|
L∞-approximation by general linear function
|
E02RAF
|
Padé-approximants |
E02RBF
|
Evaluation of fitted rational function as computed by E02RAF |
E02ZAF
|
Sort two-dimensional data into panels for fitting bicubic splines |
E04: Minimizing or Maximizing a Function
Chapter Introduction |
E04ABF
|
Minimum, function of one variable using function values only
|
E04BBF
|
Minimum, function of one variable, using first derivative |
E04CCF
|
Unconstrained minimum, simplex algorithm, function of several variables using function values only (comprehensive)
|
E04DGF
|
Unconstrained minimum, preconditioned conjugate gradient algorithm, function of several variables using first derivatives (comprehensive)
|
E04DJF
|
Read optional parameter values for E04DGF from external file
|
E04DKF
|
Supply optional parameter values to E04DGF |
E04FCF
|
Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using function values only (comprehensive)
|
E04FYF
|
Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using function values only (easy-to-use)
|
E04GBF
|
Unconstrained minimum of a sum of squares, combined Gauss–Newton and quasi-Newton algorithm using first derivatives (comprehensive)
|
E04GDF
|
Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using first derivatives (comprehensive)
|
E04GYF
|
Unconstrained minimum of a sum of squares, combined Gauss–Newton and quasi-Newton algorithm, using first derivatives (easy-to-use)
|
E04GZF
|
Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm using first derivatives (easy-to-use)
|
E04HCF
|
Check user's routine for calculating first derivatives of function
|
E04HDF
|
Check user's routine for calculating second derivatives of function
|
E04HEF
|
Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm, using second derivatives (comprehensive)
|
E04HYF
|
Unconstrained minimum of a sum of squares, combined Gauss–Newton and modified Newton algorithm, using second derivatives (easy-to-use)
|
E04JYF
|
Minimum, function of several variables, quasi-Newton algorithm, simple bounds, using function values only (easy-to-use)
|
E04KDF
|
Minimum, function of several variables, modified Newton algorithm, simple bounds, using first derivatives (comprehensive)
|
E04KYF
|
Minimum, function of several variables, quasi-Newton algorithm, simple bounds, using first derivatives (easy-to-use)
|
E04KZF
|
Minimum, function of several variables, modified Newton algorithm, simple bounds, using first derivatives (easy-to-use)
|
E04LBF
|
Minimum, function of several variables, modified Newton algorithm, simple bounds, using first and second derivatives (comprehensive)
|
E04LYF
|
Minimum, function of several variables, modified Newton algorithm, simple bounds, using first and second derivatives (easy-to-use)
|
E04MFF
|
LP problem (dense)
|
E04MGF
|
Read optional parameter values for E04MFF from external file
|
E04MHF
|
Supply optional parameter values to E04MFF |
E04MZF
|
Converts MPSX data file defining LP or QP problem to format required by E04NKF |
E04NCF
|
Convex QP problem or linearly-constrained linear least-squares problem (dense)
|
E04NDF
|
Read optional parameter values for E04NCF from external file
|
E04NEF
|
Supply optional parameter values to E04NCF |
E04NFF
|
QP problem (dense)
|
E04NGF
|
Read optional parameter values for E04NFF from external file
|
E04NHF
|
Supply optional parameter values to E04NFF |
E04NKF
|
LP or QP problem (sparse)
|
E04NLF
|
Read optional parameter values for E04NKF from external file
|
E04NMF
|
Supply optional parameter values to E04NKF |
E04UCF
|
Minimum, function of several variables, sequential QP method, nonlinear constraints, using function values and optionally first derivatives (forward communication, comprehensive)
|
E04UDF
|
Read optional parameter values for E04UCF or E04UFF from external file
|
E04UEF
|
Supply optional parameter values to E04UCF or E04UFF |
E04UFF
|
Minimum, function of several variables, sequential QP method, nonlinear constraints, using function values and optionally first derivatives (reverse communication, comprehensive)
|
E04UGF
|
NLP problem (sparse)
|
E04UHF
|
Read optional parameter values for E04UGF from external file
|
E04UJF
|
Supply optional parameter values to E04UGF |
E04UNF * |
Minimum of a sum of squares, nonlinear constraints, sequential QP method, using function values and optionally first derivatives (comprehensive) |
E04UQF
|
Read optional parameter values for E04UNF from external file
|
E04URF
|
Supply optional parameter values to E04UNF |
E04USF
|
Minimum of a sum of squares, nonlinear constraints, sequential QP method, using function values and optionally first derivatives (comprehensive)
|
E04WBF
|
Initialization routine for E04DGA, E04MFA, E04NCA, E04NFA, E04NKA, E04UCA, E04UFA, E04UGA and E04USA |
E04XAF
|
Estimate (using numerical differentiation) gradient and/or Hessian of a function
|
E04YAF
|
Check user's routine for calculating Jacobian of first derivatives |
E04YBF
|
Check user's routine for calculating Hessian of a sum of squares |
E04YCF
|
Covariance matrix for nonlinear least-squares problem (unconstrained)
|
E04ZCF
|
Check user's routines for calculating first derivatives of function and constraints |
F: Linear Algebra
F01: Matrix Factorizations
F02: Eigenvalues and Eigenvectors
F03: Determinants
F04: Simultaneous Linear Equations
Chapter Introduction |
F04AAF
|
Solution of real simultaneous linear equations with multiple right-hand sides (Black Box)
|
F04ABF
|
Solution of real symmetric positive-definite simultaneous linear equations with multiple right-hand sides using iterative refinement (Black Box)
|
F04ACF
|
Solution of real symmetric positive-definite banded simultaneous linear equations with multiple right-hand sides (Black Box)
|
F04ADF
|
Solution of complex simultaneous linear equations with multiple right-hand sides (Black Box)
|
F04AEF
|
Solution of real simultaneous linear equations with multiple right-hand sides using iterative refinement (Black Box)
|
F04AFF
|
Solution of real symmetric positive-definite simultaneous linear equations using iterative refinement (coefficient matrix already factorized by F03AEF)
|
F04AGF
|
Solution of real symmetric positive-definite simultaneous linear equations (coefficient matrix already factorized by F03AEF)
|
F04AHF
|
Solution of real simultaneous linear equations using iterative refinement (coefficient matrix already factorized by F03AFF)
|
F04AJF
|
Solution of real simultaneous linear equations (coefficient matrix already factorized by F03AFF)
|
F04AMF
|
Least-squares solution of m real equations in n unknowns, rank = n, m ≥ n using iterative refinement (Black Box)
|
F04ARF
|
Solution of real simultaneous linear equations, one right-hand side (Black Box)
|
F04ASF
|
Solution of real symmetric positive-definite simultaneous linear equations, one right-hand side using iterative refinement (Black Box)
|
F04ATF
|
Solution of real simultaneous linear equations, one right-hand side using iterative refinement (Black Box)
|
F04AXF
|
Solution of real sparse simultaneous linear equations (coefficient matrix already factorized)
|
F04EAF
|
Solution of real tridiagonal simultaneous linear equations, one right-hand side (Black Box)
|
F04FAF
|
Solution of real symmetric positive-definite tridiagonal simultaneous linear equations, one right-hand side (Black Box)
|
F04FEF
|
Solution of the Yule–Walker equations for real symmetric positive-definite Toeplitz matrix, one right-hand side
|
F04FFF
|
Solution of real symmetric positive-definite Toeplitz system, one right-hand side
|
F04JAF
|
Minimal least-squares solution of m real equations in n unknowns, rank ≤ n, m ≥ n |
F04JDF
|
Minimal least-squares solution of m real equations in n unknowns, rank ≤ n, m ≥ n |
F04JGF
|
Least-squares (if rank = n) or minimal least-squares (if rank < n) solution of m real equations in n unknowns, rank ≤ n, m ≥ n |
F04JLF
|
Real general Gauss–Markov linear model (including weighted least-squares)
|
F04JMF
|
Equality-constrained real linear least-squares problem
|
F04KLF
|
Complex general Gauss–Markov linear model (including weighted least-squares)
|
F04KMF
|
Equality-constrained complex linear least-squares problem
|
F04LEF
|
Solution of real tridiagonal simultaneous linear equations (coefficient matrix already factorized by F01LEF)
|
F04LHF
|
Solution of real almost block diagonal simultaneous linear equations (coefficient matrix already factorized by F01LHF)
|
F04MCF
|
Solution of real symmetric positive-definite variable-bandwidth simultaneous linear equations (coefficient matrix already factorized by F01MCF)
|
F04MEF
|
Update solution of the Yule–Walker equations for real symmetric positive-definite Toeplitz matrix
|
F04MFF
|
Update solution of real symmetric positive-definite Toeplitz system |
F04QAF
|
Sparse linear least-squares problem, m real equations in n unknowns
|
F04YAF
|
Covariance matrix for linear least-squares problems, m real equations in n unknowns
|
F04YCF
|
Norm estimation (for use in condition estimation), real matrix
|
F04ZCF
|
Norm estimation (for use in condition estimation), complex matrix
|
F05: Orthogonalisation
F06: Linear Algebra Support Routines
Chapter Introduction |
F06AAF
|
Generate real plane rotation |
F06BAF
|
Generate real plane rotation, storing tangent |
F06BCF
|
Recover cosine and sine from given real tangent |
F06BEF
|
Generate real Jacobi plane rotation |
F06BHF
|
Apply real similarity rotation to 2 by 2 symmetric matrix
|
F06BLF
|
Compute quotient of two real scalars, with overflow flag
|
F06BMF
|
Compute Euclidean norm from scaled form
|
F06BNF
|
Compute square root of (a2 + b2), real a and b |
F06BPF
|
Compute eigenvalue of 2 by 2 real symmetric matrix
|
F06CAF
|
Generate complex plane rotation, storing tangent, real cosine |
F06CBF
|
Generate complex plane rotation, storing tangent, real sine |
F06CCF
|
Recover cosine and sine from given complex tangent, real cosine |
F06CDF
|
Recover cosine and sine from given complex tangent, real sine |
F06CHF
|
Apply complex similarity rotation to 2 by 2 Hermitian matrix
|
F06CLF
|
Compute quotient of two complex scalars, with overflow flag
|
F06DBF
|
Broadcast scalar into integer vector |
F06DFF
|
Copy integer vector |
F06EAF
|
Dot product of two real vectors |
F06ECF
|
Add scalar times real vector to real vector |
F06EDF
|
Multiply real vector by scalar |
F06EFF
|
Copy real vector |
F06EGF
|
Swap two real vectors |
F06EJF
|
Compute Euclidean norm of real vector |
F06EKF
|
Sum absolute values of real vector elements
|
F06EPF
|
Apply real plane rotation |
F06ERF
|
Dot product of two real sparse vectors |
F06ETF
|
Add scalar times real sparse vector to real sparse vector |
F06EUF
|
Gather real sparse vector |
F06EVF
|
Gather and set to zero real sparse vector |
F06EWF
|
Scatter real sparse vector |
F06EXF
|
Apply plane rotation to two real sparse vectors |
F06FAF
|
Compute cosine of angle between two real vectors |
F06FBF
|
Broadcast scalar into real vector |
F06FCF
|
Multiply real vector by diagonal matrix
|
F06FDF
|
Multiply real vector by scalar, preserving input vector |
F06FGF
|
Negate real vector |
F06FJF
|
Update Euclidean norm of real vector in scaled form
|
F06FKF
|
Compute weighted Euclidean norm of real vector |
F06FLF
|
Elements of real vector with largest and smallest absolute value
|
F06FPF
|
Apply real symmetric plane rotation to two vectors |
F06FQF
|
Generate sequence of real plane rotations |
F06FRF
|
Generate real elementary reflection, NAG style
|
F06FSF
|
Generate real elementary reflection, LINPACK style
|
F06FTF
|
Apply real elementary reflection, NAG style
|
F06FUF
|
Apply real elementary reflection, LINPACK style
|
F06GAF
|
Dot product of two complex vectors, unconjugated |
F06GBF
|
Dot product of two complex vectors, conjugated |
F06GCF
|
Add scalar times complex vector to complex vector |
F06GDF
|
Multiply complex vector by complex scalar |
F06GFF
|
Copy complex vector |
F06GGF
|
Swap two complex vectors |
F06GRF
|
Dot product of two complex sparse vector, unconjugated |
F06GSF
|
Dot product of two complex sparse vector, conjugated |
F06GTF
|
Add scalar times complex sparse vector to complex sparse vector |
F06GUF
|
Gather complex sparse vector |
F06GVF
|
Gather and set to zero complex sparse vector |
F06GWF
|
Scatter complex sparse vector |
F06HBF
|
Broadcast scalar into complex vector |
F06HCF
|
Multiply complex vector by complex diagonal matrix
|
F06HDF
|
Multiply complex vector by complex scalar, preserving input vector |
F06HGF
|
Negate complex vector |
F06HPF
|
Apply complex plane rotation |
F06HQF
|
Generate sequence of complex plane rotations |
F06HRF
|
Generate complex elementary reflection |
F06HTF
|
Apply complex elementary reflection |
F06JDF
|
Multiply complex vector by real scalar |
F06JJF
|
Compute Euclidean norm of complex vector |
F06JKF
|
Sum absolute values of complex vector elements
|
F06JLF
|
Index, real vector element with largest absolute value
|
F06JMF
|
Index, complex vector element with largest absolute value
|
F06KCF
|
Multiply complex vector by real diagonal matrix
|
F06KDF
|
Multiply complex vector by real scalar, preserving input vector |
F06KFF
|
Copy real vector to complex vector |
F06KJF
|
Update Euclidean norm of complex vector in scaled form
|
F06KLF
|
Last non-negligible element of real vector |
F06KPF
|
Apply real plane rotation to two complex vectors |
F06PAF
|
Matrix-vector product, real rectangular matrix
|
F06PBF
|
Matrix-vector product, real rectangular band matrix
|
F06PCF
|
Matrix-vector product, real symmetric matrix
|
F06PDF
|
Matrix-vector product, real symmetric band matrix
|
F06PEF
|
Matrix-vector product, real symmetric packed matrix
|
F06PFF
|
Matrix-vector product, real triangular matrix
|
F06PGF
|
Matrix-vector product, real triangular band matrix
|
F06PHF
|
Matrix-vector product, real triangular packed matrix
|
F06PJF
|
System of equations, real triangular matrix
|
F06PKF
|
System of equations, real triangular band matrix
|
F06PLF
|
System of equations, real triangular packed matrix
|
F06PMF
|
Rank-1 update, real rectangular matrix
|
F06PPF
|
Rank-1 update, real symmetric matrix
|
F06PQF
|
Rank-1 update, real symmetric packed matrix
|
F06PRF
|
Rank-2 update, real symmetric matrix
|
F06PSF
|
Rank-2 update, real symmetric packed matrix
|
F06QFF
|
Matrix copy, real rectangular or trapezoidal matrix
|
F06QHF
|
Matrix initialisation, real rectangular matrix
|
F06QJF
|
Permute rows or columns, real rectangular matrix, permutations represented by an integer array
|
F06QKF
|
Permute rows or columns, real rectangular matrix, permutations represented by a real array
|
F06QMF
|
Orthogonal similarity transformation of real symmetric matrix as a sequence of plane rotations |
F06QPF
|
QR factorization by sequence of plane rotations, rank-1 update of real upper triangular matrix
|
F06QQF
|
QR factorization by sequence of plane rotations, real upper triangular matrix augmented by a full row
|
F06QRF
|
QR or RQ factorization by sequence of plane rotations, real upper Hessenberg matrix
|
F06QSF
|
QR or RQ factorization by sequence of plane rotations, real upper spiked matrix
|
F06QTF
|
QR factorization of UZ or RQ factorization of ZU, U real upper triangular, Z a sequence of plane rotations |
F06QVF
|
Compute upper Hessenberg matrix by sequence of plane rotations, real upper triangular matrix
|
F06QWF
|
Compute upper spiked matrix by sequence of plane rotations, real upper triangular matrix
|
F06QXF
|
Apply sequence of plane rotations, real rectangular matrix
|
F06RAF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, real general matrix
|
F06RBF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, real band matrix
|
F06RCF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, real symmetric matrix
|
F06RDF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, real symmetric matrix, packed storage
|
F06REF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, real symmetric band matrix
|
F06RJF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, real trapezoidal/triangular matrix
|
F06RKF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, real triangular matrix, packed storage
|
F06RLF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, real triangular band matrix
|
F06RMF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, real Hessenberg matrix
|
F06SAF
|
Matrix-vector product, complex rectangular matrix
|
F06SBF
|
Matrix-vector product, complex rectangular band matrix
|
F06SCF
|
Matrix-vector product, complex Hermitian matrix
|
F06SDF
|
Matrix-vector product, complex Hermitian band matrix
|
F06SEF
|
Matrix-vector product, complex Hermitian packed matrix
|
F06SFF
|
Matrix-vector product, complex triangular matrix
|
F06SGF
|
Matrix-vector product, complex triangular band matrix
|
F06SHF
|
Matrix-vector product, complex triangular packed matrix
|
F06SJF
|
System of equations, complex triangular matrix
|
F06SKF
|
System of equations, complex triangular band matrix
|
F06SLF
|
System of equations, complex triangular packed matrix
|
F06SMF
|
Rank-1 update, complex rectangular matrix, unconjugated vector |
F06SNF
|
Rank-1 update, complex rectangular matrix, conjugated vector |
F06SPF
|
Rank-1 update, complex Hermitian matrix
|
F06SQF
|
Rank-1 update, complex Hermitian packed matrix
|
F06SRF
|
Rank-2 update, complex Hermitian matrix
|
F06SSF
|
Rank-2 update, complex Hermitian packed matrix
|
F06TFF
|
Matrix copy, complex rectangular or trapezoidal matrix
|
F06THF
|
Matrix initialisation, complex rectangular matrix
|
F06TMF
|
Unitary similarity transformation of Hermitian matrix as a sequence of plane rotations |
F06TPF
|
QR factorization by sequence of plane rotations, rank-1 update of complex upper triangular matrix
|
F06TQF
|
QR × k factorization by sequence of plane rotations, complex upper triangular matrix augmented by a full row
|
F06TRF
|
QR or RQ factorization by sequence of plane rotations, complex upper Hessenberg matrix
|
F06TSF
|
QR or RQ factorization by sequence of plane rotations, complex upper spiked matrix
|
F06TTF
|
QR factorization of UZ or RQ factorization of ZU, U complex upper triangular, Z a sequence of plane rotations |
F06TVF
|
Compute upper Hessenberg matrix by sequence of plane rotations, complex upper triangular matrix
|
F06TWF
|
Compute upper spiked matrix by sequence of plane rotations, complex upper triangular matrix
|
F06TXF
|
Apply sequence of plane rotations, complex rectangular matrix, real cosine and complex sine |
F06TYF
|
Apply sequence of plane rotations, complex rectangular matrix, complex cosine and real sine |
F06UAF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, complex general matrix
|
F06UBF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, complex band matrix
|
F06UCF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, complex Hermitian matrix
|
F06UDF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, complex Hermitian matrix, packed storage
|
F06UEF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, complex Hermitian band matrix
|
F06UFF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, complex symmetric matrix
|
F06UGF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, complex symmetric matrix, packed storage
|
F06UHF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, complex symmetric band matrix
|
F06UJF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, complex trapezoidal/triangular matrix
|
F06UKF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, complex triangular matrix, packed storage
|
F06ULF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, complex triangular band matrix
|
F06UMF
|
1-norm, ∞-norm, Frobenius norm, largest absolute element, complex Hessenberg matrix
|
F06VJF
|
Permute rows or columns, complex rectangular matrix, permutations represented by an integer array
|
F06VKF
|
Permute rows or columns, complex rectangular matrix, permutations represented by a real array
|
F06VXF
|
Apply sequence of plane rotations, complex rectangular matrix, real cosine and sine |
F06YAF
|
Matrix-matrix product, two real rectangular matrices
|
F06YCF
|
Matrix-matrix product, one real symmetric matrix, one real rectangular matrix
|
F06YFF
|
Matrix-matrix product, one real triangular matrix, one real rectangular matrix
|
F06YJF
|
Solves system of equations with multiple right-hand sides, real triangular coefficient matrix
|
F06YPF
|
Rank-k update of real symmetric matrix
|
F06YRF
|
Rank-2k update of real symmetric matrix
|
F06ZAF
|
Matrix-matrix product, two complex rectangular matrices
|
F06ZCF
|
Matrix-matrix product, one complex Hermitian matrix, one complex rectangular matrix
|
F06ZFF
|
Matrix-matrix product, one complex triangular matrix, one complex rectangular matrix
|
F06ZJF
|
Solves system of equations with multiple right-hand sides, complex triangular coefficient matrix
|
F06ZPF
|
Rank-k update of complex Hermitian matrix
|
F06ZRF
|
Rank-2k update of complex Hermitian matrix
|
F06ZTF
|
Matrix-matrix product, one complex symmetric matrix, one complex rectangular matrix
|
F06ZUF
|
Rank-k update of complex symmetric matrix
|
F06ZWF
|
Rank-2k update of complex symmetric matrix
|
F07: Linear Equations (LAPACK)
A list of the LAPACK equivalent names is included in the
Chapter F07 Introduction.
Chapter Introduction |
F07ADF
|
LU factorization of real m by n matrix
|
F07AEF
|
Solution of real system of linear equations, multiple right-hand sides, matrix already factorized by F07ADF |
F07AGF
|
Estimate condition number of real matrix, matrix already factorized by F07ADF |
F07AHF
|
Refined solution with error bounds of real system of linear equations, multiple right-hand sides
|
F07AJF
|
Inverse of real matrix, matrix already factorized by F07ADF |
F07ARF
|
LU factorization of complex m by n matrix
|
F07ASF
|
Solution of complex system of linear equations, multiple right-hand sides, matrix already factorized by F07ARF |
F07AUF
|
Estimate condition number of complex matrix, matrix already factorized by F07ARF |
F07AVF
|
Refined solution with error bounds of complex system of linear equations, multiple right-hand sides
|
F07AWF
|
Inverse of complex matrix, matrix already factorized by F07ARF |
F07BDF
|
LU factorization of real m by n band matrix
|
F07BEF
|
Solution of real band system of linear equations, multiple right-hand sides, matrix already factorized by F07BDF |
F07BGF
|
Estimate condition number of real band matrix, matrix already factorized by F07BDF |
F07BHF
|
Refined solution with error bounds of real band system of linear equations, multiple right-hand sides
|
F07BRF
|
LU factorization of complex m by n band matrix
|
F07BSF
|
Solution of complex band system of linear equations, multiple right-hand sides, matrix already factorized by F07BRF |
F07BUF
|
Estimate condition number of complex band matrix, matrix already factorized by F07BRF |
F07BVF
|
Refined solution with error bounds of complex band system of linear equations, multiple right-hand sides
|
F07FDF
|
Cholesky factorization of real symmetric positive-definite matrix
|
F07FEF
|
Solution of real symmetric positive-definite system of linear equations, multiple right-hand sides, matrix already factorized by F07FDF |
F07FGF
|
Estimate condition number of real symmetric positive-definite matrix, matrix already factorized by F07FDF |
F07FHF
|
Refined solution with error bounds of real symmetric positive-definite system of linear equations, multiple right-hand sides
|
F07FJF
|
Inverse of real symmetric positive-definite matrix, matrix already factorized by F07FDF |
F07FRF
|
Cholesky factorization of complex Hermitian positive-definite matrix
|
F07FSF
|
Solution of complex Hermitian positive-definite system of linear equations, multiple right-hand sides, matrix already factorized by F07FRF |
F07FUF
|
Estimate condition number of complex Hermitian positive-definite matrix, matrix already factorized by F07FRF |
F07FVF
|
Refined solution with error bounds of complex Hermitian positive-definite system of linear equations, multiple right-hand sides
|
F07FWF
|
Inverse of complex Hermitian positive-definite matrix, matrix already factorized by F07FRF |
F07GDF
|
Cholesky factorization of real symmetric positive-definite matrix, packed storage
|
F07GEF
|
Solution of real symmetric positive-definite system of linear equations, multiple right-hand sides, matrix already factorized by F07GDF, packed storage
|
F07GGF
|
Estimate condition number of real symmetric positive-definite matrix, matrix already factorized by F07GDF, packed storage
|
F07GHF
|
Refined solution with error bounds of real symmetric positive-definite system of linear equations, multiple right-hand sides, packed storage
|
F07GJF
|
Inverse of real symmetric positive-definite matrix, matrix already factorized by F07GDF, packed storage
|
F07GRF
|
Cholesky factorization of complex Hermitian positive-definite matrix, packed storage
|
F07GSF
|
Solution of complex Hermitian positive-definite system of linear equations, multiple right-hand sides, matrix already factorized by F07GRF, packed storage
|
F07GUF
|
Estimate condition number of complex Hermitian positive-definite matrix, matrix already factorized by F07GRF, packed storage
|
F07GVF
|
Refined solution with error bounds of complex Hermitian positive-definite system of linear equations, multiple right-hand sides, packed storage
|
F07GWF
|
Inverse of complex Hermitian positive-definite matrix, matrix already factorized by F07GRF, packed storage
|
F07HDF
|
Cholesky factorization of real symmetric positive-definite band matrix
|
F07HEF
|
Solution of real symmetric positive-definite band system of linear equations, multiple right-hand sides, matrix already factorized by F07HDF |
F07HGF
|
Estimate condition number of real symmetric positive-definite band matrix, matrix already factorized by F07HDF |
F07HHF
|
Refined solution with error bounds of real symmetric positive-definite band system of linear equations, multiple right-hand sides
|
F07HRF
|
Cholesky factorization of complex Hermitian positive-definite band matrix
|
F07HSF
|
Solution of complex Hermitian positive-definite band system of linear equations, multiple right-hand sides, matrix already factorized by F07HRF |
F07HUF
|
Estimate condition number of complex Hermitian positive-definite band matrix, matrix already factorized by F07HRF |
F07HVF
|
Refined solution with error bounds of complex Hermitian positive-definite band system of linear equations, multiple right-hand sides
|
F07MDF
|
Bunch–Kaufman factorization of real symmetric indefinite matrix
|
F07MEF
|
Solution of real symmetric indefinite system of linear equations, multiple right-hand sides, matrix already factorized by F07MDF |
F07MGF
|
Estimate condition number of real symmetric indefinite matrix, matrix already factorized by F07MDF |
F07MHF
|
Refined solution with error bounds of real symmetric indefinite system of linear equations, multiple right-hand sides
|
F07MJF
|
Inverse of real symmetric indefinite matrix, matrix already factorized by F07MDF |
F07MRF
|
Bunch–Kaufman factorization of complex Hermitian indefinite matrix
|
F07MSF
|
Solution of complex Hermitian indefinite system of linear equations, multiple right-hand sides, matrix already factorized by F07MRF |
F07MUF
|
Estimate condition number of complex Hermitian indefinite matrix, matrix already factorized by F07MRF |
F07MVF
|
Refined solution with error bounds of complex Hermitian indefinite system of linear equations, multiple right-hand sides
|
F07MWF
|
Inverse of complex Hermitian indefinite matrix, matrix already factorized by F07MRF |
F07NRF
|
Bunch–Kaufman factorization of complex symmetric matrix
|
F07NSF
|
Solution of complex symmetric system of linear equations, multiple right-hand sides, matrix already factorized by F07NRF |
F07NUF
|
Estimate condition number of complex symmetric matrix, matrix already factorized by F07NRF |
F07NVF
|
Refined solution with error bounds of complex symmetric system of linear equations, multiple right-hand sides
|
F07NWF
|
Inverse of complex symmetric matrix, matrix already factorized by F07NRF |
F07PDF
|
Bunch–Kaufman factorization of real symmetric indefinite matrix, packed storage
|
F07PEF
|
Solution of real symmetric indefinite system of linear equations, multiple right-hand sides, matrix already factorized by F07PDF, packed storage
|
F07PGF
|
Estimate condition number of real symmetric indefinite matrix, matrix already factorized by F07PDF, packed storage
|
F07PHF
|
Refined solution with error bounds of real symmetric indefinite system of linear equations, multiple right-hand sides, packed storage
|
F07PJF
|
Inverse of real symmetric indefinite matrix, matrix already factorized by F07PDF, packed storage
|
F07PRF
|
Bunch–Kaufman factorization of complex Hermitian indefinite matrix, packed storage
|
F07PSF
|
Solution of complex Hermitian indefinite system of linear equations, multiple right-hand sides, matrix already factorized by F07PRF, packed storage
|
F07PUF
|
Estimate condition number of complex Hermitian indefinite matrix, matrix already factorized by F07PRF, packed storage
|
F07PVF
|
Refined solution with error bounds of complex Hermitian indefinite system of linear equations, multiple right-hand sides, packed storage
|
F07PWF
|
Inverse of complex Hermitian indefinite matrix, matrix already factorized by F07PRF, packed storage
|
F07QRF
|
Bunch–Kaufman factorization of complex symmetric matrix, packed storage
|
F07QSF
|
Solution of complex symmetric system of linear equations, multiple right-hand sides, matrix already factorized by F07QRF, packed storage
|
F07QUF
|
Estimate condition number of complex symmetric matrix, matrix already factorized by F07QRF, packed storage
|
F07QVF
|
Refined solution with error bounds of complex symmetric system of linear equations, multiple right-hand sides, packed storage
|
F07QWF
|
Inverse of complex symmetric matrix, matrix already factorized by F07QRF, packed storage
|
F07TEF
|
Solution of real triangular system of linear equations, multiple right-hand sides
|
F07TGF
|
Estimate condition number of real triangular matrix
|
F07THF
|
Error bounds for solution of real triangular system of linear equations, multiple right-hand sides
|
F07TJF
|
Inverse of real triangular matrix
|
F07TSF
|
Solution of complex triangular system of linear equations, multiple right-hand sides
|
F07TUF
|
Estimate condition number of complex triangular matrix
|
F07TVF
|
Error bounds for solution of complex triangular system of linear equations, multiple right-hand sides
|
F07TWF
|
Inverse of complex triangular matrix
|
F07UEF
|
Solution of real triangular system of linear equations, multiple right-hand sides, packed storage
|
F07UGF
|
Estimate condition number of real triangular matrix, packed storage
|
F07UHF
|
Error bounds for solution of real triangular system of linear equations, multiple right-hand sides, packed storage
|
F07UJF
|
Inverse of real triangular matrix, packed storage
|
F07USF
|
Solution of complex triangular system of linear equations, multiple right-hand sides, packed storage
|
F07UUF
|
Estimate condition number of complex triangular matrix, packed storage
|
F07UVF
|
Error bounds for solution of complex triangular system of linear equations, multiple right-hand sides, packed storage
|
F07UWF
|
Inverse of complex triangular matrix, packed storage
|
F07VEF
|
Solution of real band triangular system of linear equations, multiple right-hand sides
|
F07VGF
|
Estimate condition number of real band triangular matrix
|
F07VHF
|
Error bounds for solution of real band triangular system of linear equations, multiple right-hand sides
|
F07VSF
|
Solution of complex band triangular system of linear equations, multiple right-hand sides
|
F07VUF
|
Estimate condition number of complex band triangular matrix
|
F07VVF
|
Error bounds for solution of complex band triangular system of linear equations, multiple right-hand sides
|
F08: Least-squares and Eigenvalue Problems (LAPACK)
A list of the LAPACK equivalent names is included in the
Chapter F08 Introduction.
Chapter Introduction |
F08AEF
|
QR factorization of real general rectangular matrix
|
F08AFF
|
Form all or part of orthogonal Q from QR factorization determined by F08AEF or F08BEF |
F08AGF
|
Apply orthogonal transformation determined by F08AEF or F08BEF |
F08AHF
|
LQ factorization of real general rectangular matrix
|
F08AJF
|
Form all or part of orthogonal Q from LQ factorization determined by F08AHF |
F08AKF
|
Apply orthogonal transformation determined by F08AHF |
F08ASF
|
QR factorization of complex general rectangular matrix
|
F08ATF
|
Form all or part of unitary Q from QR factorization determined by F08ASF or F08BSF |
F08AUF
|
Apply unitary transformation determined by F08ASF or F08BSF |
F08AVF
|
LQ factorization of complex general rectangular matrix
|
F08AWF
|
Form all or part of unitary Q from LQ factorization determined by F08AVF |
F08AXF
|
Apply unitary transformation determined by F08AVF |
F08BEF
|
QR factorization of real general rectangular matrix with column pivoting |
F08BSF
|
QR factorization of complex general rectangular matrix with column pivoting |
F08FCF
|
All eigenvalues and optionally all eigenvectors of real symmetric matrix, using divide and conquer
|
F08FEF
|
Orthogonal reduction of real symmetric matrix to symmetric tridiagonal form
|
F08FFF
|
Generate orthogonal transformation matrix from reduction to tridiagonal form determined by F08FEF |
F08FGF
|
Apply orthogonal transformation determined by F08FEF |
F08FQF
|
All eigenvalues and optionally all eigenvectors of complex Hermitian matrix, using divide and conquer
|
F08FSF
|
Unitary reduction of complex Hermitian matrix to real symmetric tridiagonal form
|
F08FTF
|
Generate unitary transformation matrix from reduction to tridiagonal form determined by F08FSF |
F08FUF
|
Apply unitary transformation matrix determined by F08FSF |
F08GCF
|
All eigenvalues and optionally all eigenvectors of real symmetric matrix, packed storage, using divide and conquer
|
F08GEF
|
Orthogonal reduction of real symmetric matrix to symmetric tridiagonal form, packed storage
|
F08GFF
|
Generate orthogonal transformation matrix from reduction to tridiagonal form determined by F08GEF |
F08GGF
|
Apply orthogonal transformation determined by F08GEF |
F08GQF
|
All eigenvalues and optionally all eigenvectors of complex Hermitian matrix, packed storage, using divide and conquer
|
F08GSF
|
Unitary reduction of complex Hermitian matrix to real symmetric tridiagonal form, packed storage
|
F08GTF
|
Generate unitary transformation matrix from reduction to tridiagonal form determined by F08GSF |
F08GUF
|
Apply unitary transformation matrix determined by F08GSF |
F08HCF
|
All eigenvalues and optionally all eigenvectors of real symmetric band matrix, using divide and conquer
|
F08HEF
|
Orthogonal reduction of real symmetric band matrix to symmetric tridiagonal form
|
F08HQF
|
All eigenvalues and optionally all eigenvectors of complex Hermitian band matrix, using divide and conquer
|
F08HSF
|
Unitary reduction of complex Hermitian band matrix to real symmetric tridiagonal form
|
F08JCF
|
All eigenvalues and optionally all eigenvectors of real symmetric tridiagonal matrix, using divide and conquer
|
F08JEF
|
All eigenvalues and eigenvectors of real symmetric tridiagonal matrix, reduced from real symmetric matrix using implicit QL or QR |
F08JFF
|
All eigenvalues of real symmetric tridiagonal matrix, root-free variant of QL or QR |
F08JGF
|
All eigenvalues and eigenvectors of real symmetric positive-definite tridiagonal matrix, reduced from real symmetric positive-definite matrix
|
F08JJF
|
Selected eigenvalues of real symmetric tridiagonal matrix by bisection |
F08JKF
|
Selected eigenvectors of real symmetric tridiagonal matrix by inverse iteration, storing eigenvectors in real array
|
F08JSF
|
All eigenvalues and eigenvectors of real symmetric tridiagonal matrix, reduced from complex Hermitian matrix, using implicit QL or QR |
F08JUF
|
All eigenvalues and eigenvectors of real symmetric positive-definite tridiagonal matrix, reduced from complex Hermitian positive-definite matrix
|
F08JXF
|
Selected eigenvectors of real symmetric tridiagonal matrix by inverse iteration, storing eigenvectors in complex array
|
F08KEF
|
Orthogonal reduction of real general rectangular matrix to bidiagonal form
|
F08KFF
|
Generate orthogonal transformation matrices from reduction to bidiagonal form determined by F08KEF |
F08KGF
|
Apply orthogonal transformations from reduction to bidiagonal form determined by F08KEF |
F08KSF
|
Unitary reduction of complex general rectangular matrix to bidiagonal form
|
F08KTF
|
Generate unitary transformation matrices from reduction to bidiagonal form determined by F08KSF |
F08KUF
|
Apply unitary transformations from reduction to bidiagonal form determined by F08KSF |
F08LEF
|
Reduction of real rectangular band matrix to upper bidiagonal form
|
F08LSF
|
Reduction of complex rectangular band matrix to upper bidiagonal form
|
F08MEF
|
SVD of real bidiagonal matrix reduced from real general matrix
|
F08MSF
|
SVD of real bidiagonal matrix reduced from complex general matrix
|
F08NEF
|
Orthogonal reduction of real general matrix to upper Hessenberg form
|
F08NFF
|
Generate orthogonal transformation matrix from reduction to Hessenberg form determined by F08NEF |
F08NGF
|
Apply orthogonal transformation matrix from reduction to Hessenberg form determined by F08NEF |
F08NHF
|
Balance real general matrix
|
F08NJF
|
Transform eigenvectors of real balanced matrix to those of original matrix supplied to F08NHF |
F08NSF
|
Unitary reduction of complex general matrix to upper Hessenberg form
|
F08NTF
|
Generate unitary transformation matrix from reduction to Hessenberg form determined by F08NSF |
F08NUF
|
Apply unitary transformation matrix from reduction to Hessenberg form determined by F08NSF |
F08NVF
|
Balance complex general matrix
|
F08NWF
|
Transform eigenvectors of complex balanced matrix to those of original matrix supplied to F08NVF |
F08PEF
|
Eigenvalues and Schur factorization of real upper Hessenberg matrix reduced from real general matrix
|
F08PKF
|
Selected right and/or left eigenvectors of real upper Hessenberg matrix by inverse iteration |
F08PSF
|
Eigenvalues and Schur factorization of complex upper Hessenberg matrix reduced from complex general matrix
|
F08PXF
|
Selected right and/or left eigenvectors of complex upper Hessenberg matrix by inverse iteration |
F08QFF
|
Reorder Schur factorization of real matrix using orthogonal similarity transformation |
F08QGF
|
Reorder Schur factorization of real matrix, form orthonormal basis of right invariant subspace for selected eigenvalues, with estimates of sensitivities |
F08QHF
|
Solve real Sylvester matrix equation AX + XB = C, A and B are upper quasi-triangular or transposes
|
F08QKF
|
Left and right eigenvectors of real upper quasi-triangular matrix
|
F08QLF
|
Estimates of sensitivities of selected eigenvalues and eigenvectors of real upper quasi-triangular matrix
|
F08QTF
|
Reorder Schur factorization of complex matrix using unitary similarity transformation |
F08QUF
|
Reorder Schur factorization of complex matrix, form orthonormal basis of right invariant subspace for selected eigenvalues, with estimates of sensitivities |
F08QVF
|
Solve complex Sylvester matrix equation AX + XB = C, A and B are upper triangular or conjugate-transposes |
F08QXF
|
Left and right eigenvectors of complex upper triangular matrix
|
F08QYF
|
Estimates of sensitivities of selected eigenvalues and eigenvectors of complex upper triangular matrix
|
F08SEF
|
Reduction to standard form of real symmetric-definite generalized eigenproblem Ax = λ Bx, ABx = λ x or BAx = λ x, B factorized by F07FDF |
F08SSF
|
Reduction to standard form of complex Hermitian-definite generalized eigenproblem Ax = λ Bx, ABx = λ x or BAx = λ x, B factorized by F07FRF |
F08TEF
|
Reduction to standard form of real symmetric-definite generalized eigenproblem Ax=λ Bx, ABx = λ x or BAx = λ x, packed storage, B factorized by F07GDF |
F08TSF
|
Reduction to standard form of complex Hermitian-definite generalized eigenproblem Ax=λ Bx, ABx = lamda x or BAx = λ x, packed storage, B factorized by F07GRF |
F08UEF
|
Reduction of real symmetric-definite banded generalized eigenproblem Ax = λ Bx to standard form Cy = λ y, such that C has the same bandwidth as A |
F08UFF
|
Computes a split Cholesky factorization of real symmetric positive-definite band matrix A |
F08USF
|
Reduction of complex Hermitian-definite banded generalized eigenproblem Ax = λ Bx to standard form Cy = λ y, such that C has the same bandwidth as A |
F08UTF
|
Computes a split Cholesky factorization of complex Hermitian positive-definite band matrix A |
F08WEF
|
Orthogonal reduction of a pair of real general matrices to generalized upper Hessenberg form
|
F08WHF
|
Balance a pair of real general matrices
|
F08WJF
|
Transform eigenvectors of a pair of real balanced matrices to those of original matrix pair supplied to F08WHF |
F08WSF
|
Unitary reduction of a pair of complex general matrices to generalized upper Hessenberg form
|
F08WVF
|
Balance a pair of complex general matrices
|
F08WWF
|
Transform eigenvectors of a pair of complex balanced matrices to those of original matrix pair supplied to F08WVF |
F08XEF
|
Eigenvalues and generalized Schur factorization of real generalized upper Hessenberg matrix reduced from a pair of real general matrices
|
F08XSF
|
Eigenvalues and generalized Schur factorization of complex generalized upper Hessenberg matrix reduced from a pair of complex general matrices
|
F08YKF
|
Left and right eigenvectors of a pair of real upper quasi-triangular matrices
|
F08YXF
|
Left and right eigenvectors of a pair of complex upper triangular matrices
|
F11: Sparse Linear Algebra
Chapter Introduction |
F11BAF ** |
Real sparse nonsymmetric linear systems, setup for F11BBF |
F11BBF ** |
Real sparse nonsymmetric linear systems, preconditioned RGMRES, CGS or Bi-CGSTAB |
F11BCF ** |
Real sparse nonsymmetric linear systems, diagnostic for F11BBF |
F11BDF
|
Real sparse nonsymmetric linear systems, setup for F11BEF |
F11BEF
|
Real sparse nonsymmetric linear systems, preconditioned RGMRES, CGS, Bi-CGSTAB or TFQMR method
|
F11BFF
|
Real sparse nonsymmetric linear systems, diagnostic for F11BEF |
F11BRF
|
Complex sparse non-Hermitian linear systems, setup for F11BSF |
F11BSF
|
Complex sparse non-Hermitian linear systems, preconditioned RGMRES, CGS,Bi-CGSTAB or TFQMR method
|
F11BTF
|
Complex sparse non-Hermitian linear systems, diagnostic for F11BSF |
F11DAF
|
Real sparse nonsymmetric linear systems, incomplete LU factorization |
F11DBF
|
Solution of linear system involving incomplete LU preconditioning matrix generated by F11DAF |
F11DCF
|
Solution of real sparse nonsymmetric linear system, RGMRES, CGS, Bi-CGSTAB or TFQMR method, preconditioner computed by F11DAF |
F11DDF
|
Solution of linear system involving preconditioning matrix generated by applying SSOR to real sparse nonsymmetric matrix
|
F11DEF
|
Solution of real sparse nonsymmetric linear system, RGMRES, CGS, Bi-CGSTAB, or TFQMR method, Jacobi or SSOR preconditioner (Black Box)
|
F11DKF
|
Real sparse nonsymmetric linear systems, line Jacobi preconditioner |
F11DNF
|
Complex sparse non-Hermitian linear systems, incomplete LU factorization |
F11DPF
|
Solution of complex linear system involving incomplete LU preconditioning matrix generated by F11DNF |
F11DQF
|
Solution of complex sparse non-Hermitian linear system, RGMRES, CGS, Bi-CGSTAB or TFQMR method, preconditioner computed by F11DNF (Black Box)
|
F11DRF
|
Solution of linear system involving preconditioning matrix generated by applying SSOR to complex sparse non-Hermitian matrix
|
F11DSF
|
Solution of complex sparse non-Hermitian linear system, RGMRES, CGS, Bi-CGSTAB or TFQMR method, Jacobi or SSOR preconditioner Black Box
|
F11DXF
|
Complex sparse nonsymmetric linear systems, line Jacobi preconditioner |
F11GAF * |
Real sparse symmetric linear systems, setup for F11GBF |
F11GBF * |
Real sparse symmetric linear systems, preconditioned conjugate gradient or Lanczos |
F11GCF * |
Real sparse symmetric linear systems, diagnostic for F11GBF |
F11GDF
|
Real sparse symmetric linear systems, setup for F11GEF |
F11GEF
|
Real sparse symmetric linear systems, preconditioned conjugate gradient or Lanczos |
F11GFF
|
Real sparse symmetric linear systems, diagnostic for F11GEF |
F11GRF
|
Complex sparse symmetric linear systems, setup for F11GEF |
F11GSF
|
Complex sparse symmetric linear systems, preconditioned conjugate gradient or Lanczos |
F11GTF
|
Complex sparse symmetric linear systems, diagnostic for F11GEF |
F11JAF
|
Real sparse symmetric matrix, incomplete Cholesky factorization |
F11JBF
|
Solution of linear system involving incomplete Cholesky preconditioning matrix generated by F11JAF |
F11JCF
|
Solution of real sparse symmetric linear system, conjugate gradient/Lanczos method, preconditioner computed by F11JAF (Black Box)
|
F11JDF
|
Solution of linear system involving preconditioning matrix generated by applying SSOR to real sparse symmetric matrix
|
F11JEF
|
Solution of real sparse symmetric linear system, conjugate gradient/Lanczos method, Jacobi or SSOR preconditioner (Black Box)
|
F11JNF
|
Complex sparse Hermitian matrix, incomplete Cholesky factorization |
F11JPF
|
Solution of complex linear system involving incomplete Cholesky preconditioning matrix generated by F11JNF |
F11JQF
|
Solution of complex sparse Hermitian linear system, conjugate gradient/Lanczos method, preconditioner computed by F11JNF (Black Box)
|
F11JRF
|
Solution of linear system involving preconditioning matrix generated by applying SSOR to complex sparse Hermitian matrix
|
F11JSF
|
Solution of complex sparse Hermitian linear system, conjugate gradient/Lanczos method, Jacobi or SSOR preconditioner (Black Box)
|
F11XAF
|
Real sparse nonsymmetric matrix vector multiply |
F11XEF
|
Real sparse symmetric matrix vector multiply |
F11XNF
|
Complex sparse non-Hermitian matrix vector multiply |
F11XSF
|
Complex sparse Hermitian matrix vector multiply |
F11ZAF
|
Real sparse nonsymmetric matrix reorder routine
|
F11ZBF
|
Real sparse symmetric matrix reorder routine
|
F11ZNF
|
Complex sparse non-Hermitian matrix reorder routine
|
F11ZPF
|
Complex sparse Hermitian matrix reorder routine
|
G01: Simple Calculations on Statistical Data
Chapter Introduction |
G01AAF
|
Mean, variance, skewness, kurtosis, etc, one variable, from raw data
|
G01ABF
|
Mean, variance, skewness, kurtosis, etc, two variables, from raw data
|
G01ADF
|
Mean, variance, skewness, kurtosis, etc, one variable, from frequency table |
G01AEF
|
Frequency table from raw data
|
G01AFF
|
Two-way contingency table analysis, with χ2/Fisher's exact test |
G01AGF
|
Lineprinter scatterplot of two variables
|
G01AHF
|
Lineprinter scatterplot of one variable against Normal scores |
G01AJF
|
Lineprinter histogram of one variable
|
G01ALF
|
Computes a five-point summary (median, hinges and extremes)
|
G01ARF
|
Constructs a stem and leaf plot |
G01ASF
|
Constructs a box and whisker plot |
G01BJF
|
Binomial distribution function
|
G01BKF
|
Poisson distribution function
|
G01BLF
|
Hypergeometric distribution function
|
G01DAF
|
Normal scores, accurate values
|
G01DBF
|
Normal scores, approximate values
|
G01DCF
|
Normal scores, approximate variance-covariance matrix
|
G01DDF
|
Shapiro and Wilk's W test for Normality |
G01DHF
|
Ranks, Normal scores, approximate Normal scores or exponential (Savage) scores |
G01EAF
|
Computes probabilities for the standard Normal distribution |
G01EBF
|
Computes probabilities for Student's t-distribution |
G01ECF
|
Computes probabilities for χ2 distribution |
G01EDF
|
Computes probabilities for F-distribution |
G01EEF
|
Computes upper and lower tail probabilities and probability density function for the beta distribution |
G01EFF
|
Computes probabilities for the gamma distribution |
G01EMF
|
Computes probability for the Studentized range statistic |
G01EPF
|
Computes bounds for the significance of a Durbin–Watson statistic |
G01ERF
|
Computes probability for von Mises distribution |
G01EYF
|
Computes probabilities for the one-sample Kolmogorov–Smirnov distribution |
G01EZF
|
Computes probabilities for the two-sample Kolmogorov–Smirnov distribution |
G01FAF
|
Computes deviates for the standard Normal distribution |
G01FBF
|
Computes deviates for Student's t-distribution |
G01FCF
|
Computes deviates for the χ2 distribution |
G01FDF
|
Computes deviates for the F-distribution |
G01FEF
|
Computes deviates for the beta distribution |
G01FFF
|
Computes deviates for the gamma distribution |
G01FMF
|
Computes deviates for the Studentized range statistic |
G01GBF
|
Computes probabilities for the non-central Student's t-distribution |
G01GCF
|
Computes probabilities for the non-central χ2 distribution |
G01GDF
|
Computes probabilities for the non-central F-distribution |
G01GEF
|
Computes probabilities for the non-central beta distribution |
G01HAF
|
Computes probability for the bivariate Normal distribution |
G01HBF
|
Computes probabilities for the multivariate Normal distribution |
G01JCF
|
Computes probability for a positive linear combination of χ2 variables
|
G01JDF
|
Computes lower tail probability for a linear combination of (central) χ2 variables
|
G01MBF
|
Computes reciprocal of Mills' Ratio
|
G01NAF
|
Cumulants and moments of quadratic forms in Normal variables
|
G01NBF
|
Moments of ratios of quadratic forms in Normal variables, and related statistics |
G02: Correlation and Regression Analysis
Chapter Introduction |
G02BAF
|
Pearson product-moment correlation coefficients, all variables, no missing values
|
G02BBF
|
Pearson product-moment correlation coefficients, all variables, casewise treatment of missing values
|
G02BCF
|
Pearson product-moment correlation coefficients, all variables, pairwise treatment of missing values
|
G02BDF
|
Correlation-like coefficients (about zero), all variables, no missing values
|
G02BEF
|
Correlation-like coefficients (about zero), all variables, casewise treatment of missing values
|
G02BFF
|
Correlation-like coefficients (about zero), all variables, pairwise treatment of missing values
|
G02BGF
|
Pearson product-moment correlation coefficients, subset of variables, no missing values
|
G02BHF
|
Pearson product-moment correlation coefficients, subset of variables, casewise treatment of missing values
|
G02BJF
|
Pearson product-moment correlation coefficients, subset of variables, pairwise treatment of missing values
|
G02BKF
|
Correlation-like coefficients (about zero), subset of variables, no missing values
|
G02BLF
|
Correlation-like coefficients (about zero), subset of variables, casewise treatment of missing values
|
G02BMF
|
Correlation-like coefficients (about zero), subset of variables, pairwise treatment of missing values
|
G02BNF
|
Kendall/Spearman non-parametric rank correlation coefficients, no missing values, overwriting input data
|
G02BPF
|
Kendall/Spearman non-parametric rank correlation coefficients, casewise treatment of missing values, overwriting input data
|
G02BQF
|
Kendall/Spearman non-parametric rank correlation coefficients, no missing values, preserving input data
|
G02BRF
|
Kendall/Spearman non-parametric rank correlation coefficients, casewise treatment of missing values, preserving input data
|
G02BSF
|
Kendall/Spearman non-parametric rank correlation coefficients, pairwise treatment of missing values
|
G02BTF
|
Update a weighted sum of squares matrix with a new observation |
G02BUF
|
Computes a weighted sum of squares matrix
|
G02BWF
|
Computes a correlation matrix from a sum of squares matrix
|
G02BXF
|
Computes (optionally weighted) correlation and covariance matrices
|
G02BYF
|
Computes partial correlation/variance-covariance matrix from correlation/variance-covariance matrix computed by G02BXF |
G02CAF
|
Simple linear regression with constant term, no missing values
|
G02CBF
|
Simple linear regression without constant term, no missing values
|
G02CCF
|
Simple linear regression with constant term, missing values
|
G02CDF
|
Simple linear regression without constant term, missing values
|
G02CEF
|
Service routines for multiple linear regression, select elements from vectors and matrices
|
G02CFF
|
Service routines for multiple linear regression, re-order elements of vectors and matrices
|
G02CGF
|
Multiple linear regression, from correlation coefficients, with constant term
|
G02CHF
|
Multiple linear regression, from correlation-like coefficients, without constant term
|
G02DAF
|
Fits a general (multiple) linear regression model |
G02DCF
|
Add/delete an observation to/from a general linear regression model |
G02DDF
|
Estimates of linear parameters and general linear regression model from updated model |
G02DEF
|
Add a new variable to a general linear regression model |
G02DFF
|
Delete a variable from a general linear regression model |
G02DGF
|
Fits a general linear regression model for new dependent variable
|
G02DKF
|
Estimates and standard errors of parameters of a general linear regression model for given constraints |
G02DNF
|
Computes estimable function of a general linear regression model and its standard error |
G02EAF
|
Computes residual sums of squares for all possible linear regressions for a set of independent variables
|
G02ECF
|
Calculates R2 and CP values from residual sums of squares |
G02EEF
|
Fits a linear regression model by forward selection
|
G02FAF
|
Calculates standardized residuals and influence statistics |
G02FCF
|
Computes Durbin–Watson test statistic |
G02GAF
|
Fits a generalized linear model with Normal errors |
G02GBF
|
Fits a generalized linear model with binomial errors |
G02GCF
|
Fits a generalized linear model with Poisson errors |
G02GDF
|
Fits a generalized linear model with gamma errors |
G02GKF
|
Estimates and standard errors of parameters of a general linear model for given constraints |
G02GNF
|
Computes estimable function of a generalized linear model and its standard error |
G02HAF
|
Robust regression, standard M-estimates |
G02HBF
|
Robust regression, compute weights for use with G02HDF |
G02HDF
|
Robust regression, compute regression with user-supplied functions and weights |
G02HFF
|
Robust regression, variance-covariance matrix following G02HDF |
G02HKF
|
Calculates a robust estimation of a correlation matrix, Huber's weight function
|
G02HLF
|
Calculates a robust estimation of a correlation matrix, user-supplied weight function plus derivatives |
G02HMF
|
Calculates a robust estimation of a correlation matrix, user-supplied weight function
|
G03: Multivariate Methods
G04: Analysis of Variance
G05: Random Number Generators
Chapter Introduction |
G05CAF * |
Pseudo-random real numbers, uniform distribution over (0,1) |
G05CBF * |
Initialise random number generating routines to give repeatable sequence |
G05CCF * |
Initialise random number generating routines to give non-repeatable sequence |
G05CFF * |
Save state of random number generating routines |
G05CGF * |
Restore state of random number generating routines |
G05DAF * |
Pseudo-random real numbers, uniform distribution over (a,b) |
G05DBF * |
Pseudo-random real numbers, (negative) exponential distribution |
G05DCF * |
Pseudo-random real numbers, logistic distribution |
G05DDF * |
Pseudo-random real numbers, Normal distribution |
G05DEF * |
Pseudo-random real numbers, log-normal distribution |
G05DFF * |
Pseudo-random real numbers, Cauchy distribution |
G05DHF * |
Pseudo-random real numbers, χ2 distribution
|
G05DJF * |
Pseudo-random real numbers, Student's t-distribution
|
G05DKF * |
Pseudo-random real numbers, F-distribution
|
G05DPF * |
Pseudo-random real numbers, Weibull distribution |
G05DRF * |
Pseudo-random integer, Poisson distribution |
G05DYF * |
Pseudo-random integer from uniform distribution |
G05DZF * |
Pseudo-random logical (boolean) value |
G05EAF * |
Set up reference vector for multivariate Normal distribution |
G05EBF * |
Set up reference vector for generating pseudo-random integers, uniform distribution |
G05ECF * |
Set up reference vector for generating pseudo-random integers, Poisson distribution |
G05EDF * |
Set up reference vector for generating pseudo-random integers, binomial distribution |
G05EEF * |
Set up reference vector for generating pseudo-random integers, negative binomial distribution |
G05EFF * |
Set up reference vector for generating pseudo-random integers, hypergeometric distribution |
G05EGF * |
Set up reference vector for univariate ARMA time series model |
G05EHF * |
Pseudo-random permutation of an integer vector |
G05EJF * |
Pseudo-random sample from an integer vector |
G05EWF * |
Generate next term from reference vector for ARMA time series model |
G05EXF * |
Set up reference vector from supplied cumulative distribution function or probability distribution function |
G05EYF * |
Pseudo-random integer from reference vector |
G05EZF * |
Pseudo-random multivariate Normal vector from reference vector |
G05FAF * |
Generates a vector of random numbers from a uniform distribution |
G05FBF * |
Generates a vector of random numbers from an (negative) exponential distribution |
G05FDF * |
Generates a vector of random numbers from a Normal distribution |
G05FEF * |
Generates a vector of pseudo-random numbers from a beta distribution |
G05FFF * |
Generates a vector of pseudo-random numbers from a gamma distribution |
G05FSF * |
Generates a vector of pseudo-random variates from von Mises distribution |
G05GAF * |
Computes a random orthogonal matrix |
G05GBF * |
Computes a random correlation matrix |
G05HDF * |
Generates a realisation of a multivariate time series from a VARMA model |
G05HKF
|
Univariate time series, generate n terms of either a symmetric GARCH process or a GARCH process with asymmetry of the form (εt-1 + γ)2 |
G05HLF
|
Univariate time series, generate n terms of a GARCH process with asymmetry of the form (|εt-1| + γ εt-1)2 |
G05HMF
|
Univariate time series, generate n terms of an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process
|
G05HNF
|
Univariate time series, generate n terms of an exponential GARCH (EGARCH) process
|
G05KAF
|
Pseudo-random real numbers, uniform distribution over (0,1), seeds and generator number passed explicitly
|
G05KBF
|
Initialise seeds of a given generator for random number generating routines (that pass seeds expicitly) to give a repeatable sequence
|
G05KCF
|
Initialise seeds of a given generator for random number generating routines (that pass seeds expicitly) to give non-repeatable sequence
|
G05KEF
|
Pseudo-random logical (boolean) value, seeds and generator number passed explicitly
|
G05LAF
|
Generates a vector of random numbers from a Normal distribution, seeds and generator number passed explicitly
|
G05LBF
|
Generates a vector of random numbers from a Student's t-distribution, seeds and generator number passed explicitly
|
G05LCF
|
Generates a vector of random numbers from a χ2 distribution, seeds and generator number passed explicitly
|
G05LDF
|
Generates a vector of random numbers from an F-distribution, seeds and generator number passed explicitly
|
G05LEF
|
Generates a vector of random numbers from a beta distribution, seeds and generator number passed explicitly
|
G05LFF
|
Generates a vector of random numbers from a γ distribution, seeds and generator number passed explicitly
|
G05LGF
|
Generates a vector of random numbers from a uniform distribution, seeds and generator number passed explicitly
|
G05LHF
|
Generates a vector of random numbers from a triangular distribution, seeds and generator number passed explicitly
|
G05LJF
|
Generates a vector of random numbers from an exponential distribution, seeds and generator number passed explicitly
|
G05LKF
|
Generates a vector of random numbers from a lognormal distribution, seeds and generator number passed explicitly
|
G05LLF
|
Generates a vector of random numbers from a Cauchy distribution, seeds and generator number passed explicitly
|
G05LMF
|
Generates a vector of random numbers from a Weibull distribution, seeds and generator number passed explicitly
|
G05LNF
|
Generates a vector of random numbers from a logistic distribution, seeds and generator number passed explicitly
|
G05LPF
|
Generates a vector of random numbers from a Von Mises distribution, seeds and generator number passed explicitly
|
G05LQF
|
Generates a vector of random numbers from an exponential mixture distribution, seeds and generator number passed explicitly
|
G05LZF
|
Generates a vector of random numbers from a multivariate Normal distribution, seeds and generator number passed explicitly
|
G05MAF
|
Generates a vector of random integers from a uniform distribution, seeds and generator number passed explicitly
|
G05MBF
|
Generates a vector of random integers from a geometric distribution, seeds and generator number passed explicitly
|
G05MCF
|
Generates a vector of random integers from a negative binomial distribution, seeds and generator number passed explicitly
|
G05MDF
|
Generates a vector of random integers from a logarithmic distribution, seeds and generator number passed explicitly
|
G05MEF
|
Generates a vector of random integers from a Poisson distribution with varying mean, seeds and generator number passed explicitly
|
G05MJF
|
Generates a vector of random integers from a binomial distribution, seeds and generator number passed explicitly
|
G05MKF
|
Generates a vector of random integers from a Poisson distribution, seeds and generator number passed explicitly
|
G05MLF
|
Generates a vector of random integers from a hypergeometric distribution, seeds and generator number passed explicitly
|
G05MRF
|
Generates a vector of random integers from a multinomial distribution, seeds and generator number passed explicitly
|
G05MZF
|
Generates a vector of random integers from a general discrete distribution, seeds and generator number passed explicitly
|
G05NAF
|
Pseudo-random permutation of an integer vector
|
G05NBF
|
Pseudo-random sample from an integer vector
|
G05PAF
|
Generates a realisation of a time series from an ARMA model
|
G05PCF
|
Generates a realisation of a multivariate time series from a VARMA model
|
G05QAF
|
Computes a random orthogonal matrix
|
G05QBF
|
Computes a random correlation matrix
|
G05QDF
|
Generates a random table matrix
|
G05YAF
|
Multi-dimensional quasi-random number generator with a uniform probability distribution |
G05YBF
|
Multi-dimensional quasi-random number generator with a Gaussian or log-normal probability distribution |
G05ZAF
|
Selects either the basic generator or the Wichmann–Hill generator for those routines using internal communication
|
G07: Univariate Estimation
Chapter Introduction |
G07AAF
|
Computes confidence interval for the parameter of a binomial distribution |
G07ABF
|
Computes confidence interval for the parameter of a Poisson distribution |
G07BBF
|
Computes maximum likelihood estimates for parameters of the Normal distribution from grouped and/or censored data
|
G07BEF
|
Computes maximum likelihood estimates for parameters of the Weibull distribution |
G07CAF
|
Computes t-test statistic for a difference in means between two Normal populations, confidence interval
|
G07DAF
|
Robust estimation, median, median absolute deviation, robust standard deviation |
G07DBF
|
Robust estimation, M-estimates for location and scale parameters, standard weight functions
|
G07DCF
|
Robust estimation, M-estimates for location and scale parameters, user-defined weight functions
|
G07DDF
|
Computes a trimmed and winsorized mean of a single sample with estimates of their variance |
G07EAF
|
Robust confidence intervals, one-sample |
G07EBF
|
Robust confidence intervals, two-sample |
G08: Nonparametric Statistics
G10: Smoothing in Statistics
G11: Contingency Table Analysis
G12: Survival Analysis
G13: Time Series Analysis
Chapter Introduction |
G13AAF
|
Univariate time series, seasonal and non-seasonal differencing |
G13ABF
|
Univariate time series, sample autocorrelation function
|
G13ACF
|
Univariate time series, partial autocorrelations from autocorrelations |
G13ADF
|
Univariate time series, preliminary estimation, seasonal ARIMA model |
G13AEF
|
Univariate time series, estimation, seasonal ARIMA model (comprehensive)
|
G13AFF
|
Univariate time series, estimation, seasonal ARIMA model (easy-to-use)
|
G13AGF
|
Univariate time series, update state set for forecasting |
G13AHF
|
Univariate time series, forecasting from state set
|
G13AJF
|
Univariate time series, state set and forecasts, from fully specified seasonal ARIMA model |
G13ASF
|
Univariate time series, diagnostic checking of residuals, following G13AEF or G13AFF |
G13AUF
|
Computes quantities needed for range-mean or standard deviation-mean plot |
G13BAF
|
Multivariate time series, filtering (pre-whitening) by an ARIMA model |
G13BBF
|
Multivariate time series, filtering by a transfer function model |
G13BCF
|
Multivariate time series, cross-correlations |
G13BDF
|
Multivariate time series, preliminary estimation of transfer function model |
G13BEF
|
Multivariate time series, estimation of multi-input model |
G13BGF
|
Multivariate time series, update state set for forecasting from multi-input model |
G13BHF
|
Multivariate time series, forecasting from state set of multi-input model |
G13BJF
|
Multivariate time series, state set and forecasts from fully specified multi-input model |
G13CAF
|
Univariate time series, smoothed sample spectrum using rectangular, Bartlett, Tukey or Parzen lag window |
G13CBF
|
Univariate time series, smoothed sample spectrum using spectral smoothing by the trapezium frequency (Daniell) window |
G13CCF
|
Multivariate time series, smoothed sample cross spectrum using rectangular, Bartlett, Tukey or Parzen lag window |
G13CDF
|
Multivariate time series, smoothed sample cross spectrum using spectral smoothing by the trapezium frequency (Daniell) window |
G13CEF
|
Multivariate time series, cross amplitude spectrum, squared coherency, bounds, univariate and bivariate (cross) spectra |
G13CFF
|
Multivariate time series, gain, phase, bounds, univariate and bivariate (cross) spectra |
G13CGF
|
Multivariate time series, noise spectrum, bounds, impulse response function and its standard error |
G13DBF
|
Multivariate time series, multiple squared partial autocorrelations |
G13DCF
|
Multivariate time series, estimation of VARMA model |
G13DJF
|
Multivariate time series, forecasts and their standard errors |
G13DKF
|
Multivariate time series, updates forecasts and their standard errors |
G13DLF
|
Multivariate time series, differences and/or transforms (for use before G13DCF)
|
G13DMF
|
Multivariate time series, sample cross-correlation or cross-covariance matrices
|
G13DNF
|
Multivariate time series, sample partial lag correlation matrices, χ2 statistics and significance levels |
G13DPF
|
Multivariate time series, partial autoregression matrices
|
G13DSF
|
Multivariate time series, diagnostic checking of residuals, following G13DCF |
G13DXF
|
Calculates the zeros of a vector autoregressive (or moving average) operator |
G13EAF
|
Combined measurement and time update, one iteration of Kalman filter, time-varying, square root covariance filter |
G13EBF
|
Combined measurement and time update, one iteration of Kalman filter, time-invariant, square root covariance filter |
G13FAF
|
Univariate time series, parameter estimation for either a symmetric GARCH process or a GARCH process with asymmetry of the form (εt-1 + γ)2 |
G13FBF
|
Univariate time series, forecast function for either a symmetric GARCH process or a GARCH process with asymmetry of the form (εt-1 + γ)2 |
G13FCF
|
Univariate time series, parameter estimation for a GARCH process with asymmetry of the form (|εt-1| + γ εt-1)2 |
G13FDF
|
Univariate time series, forecast function for a GARCH process with asymmetry of the form (|εt-1| + γ εt-1)2 |
G13FEF
|
Univariate time series, parameter estimation for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process
|
G13FFF
|
Univariate time series, forecast function for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process
|
G13FGF
|
Univariate time series, forecast function for an exponential GARCH (EGARCH) process
|
G13FHF
|
Univariate time series, forecast function for an exponential GARCH (EGARCH) process
|
H: Operations Research
M01: Sorting
Chapter Introduction |
M01CAF
|
Sort a vector, real numbers
|
M01CBF
|
Sort a vector, integer numbers
|
M01CCF
|
Sort a vector, character data
|
M01DAF
|
Rank a vector, real numbers
|
M01DBF
|
Rank a vector, integer numbers
|
M01DCF
|
Rank a vector, character data
|
M01DEF
|
Rank rows of a matrix, real numbers
|
M01DFF
|
Rank rows of a matrix, integer numbers
|
M01DJF
|
Rank columns of a matrix, real numbers
|
M01DKF
|
Rank columns of a matrix, integer numbers
|
M01DZF
|
Rank arbitrary data
|
M01EAF
|
Rearrange a vector according to given ranks, real numbers
|
M01EBF
|
Rearrange a vector according to given ranks, integer numbers
|
M01ECF
|
Rearrange a vector according to given ranks, character data
|
M01EDF
|
Rearrange a vector according to given ranks, complex numbers
|
M01ZAF
|
Invert a permutation |
M01ZBF
|
Check validity of a permutation |
M01ZCF
|
Decompose a permutation into cycles
|
P01: Error Trapping
S: Approximations of Special Functions
Chapter Introduction |
S01BAF
|
ln (1+x) |
S01EAF
|
Complex exponential, e^z |
S07AAF
|
tan x |
S09AAF
|
arcsin x |
S09ABF
|
arccos x |
S10AAF
|
tanh x |
S10ABF
|
sinh x |
S10ACF
|
cosh x |
S11AAF
|
arctanh x |
S11ABF
|
arcsinh x |
S11ACF
|
arccosh x |
S13AAF
|
Exponential integral E1 (x) |
S13ACF
|
Cosine integral Ci(x) |
S13ADF
|
Sine integral Si(x) |
S14AAF
|
Gamma function
|
S14ABF
|
Log Gamma function
|
S14ACF
|
ψ (x) - ln x |
S14ADF
|
Scaled derivatives of ψ (x) |
S14AEF
|
Polygamma function ψ(n)(x) for real x |
S14AFF
|
Polygamma function ψ(n)(z) for complex z |
S14BAF
|
Incomplete Gamma functions P(a,x) and Q(a,x) |
S15ABF
|
Cumulative Normal distribution function P(x) |
S15ACF
|
Complement of cumulative Normal distribution function Q(x) |
S15ADF
|
Complement of error function erfc(x) |
S15AEF
|
Error function erf(x) |
S15AFF
|
Dawson's integral |
S15DDF
|
Scaled complex complement of error function, exp(-z2) erfc(-iz) |
S17ACF
|
Bessel function Y0 (x) |
S17ADF
|
Bessel function Y1 (x) |
S17AEF
|
Bessel function J0 (x) |
S17AFF
|
Bessel function J1 (x) |
S17AGF
|
Airy function Ai(x) |
S17AHF
|
Airy function Bi(x) |
S17AJF
|
Airy function Ai'(x) |
S17AKF
|
Airy function Bi'(x) |
S17ALF
|
Zeros of Bessel functions Jα(x), J'α(x), Yα(x) or Y'α(x) |
S17DCF
|
Bessel functions Yν+a(z), real a ≥ 0, complex z, ν =0,1, 2,... |
S17DEF
|
Bessel functions Jν+a(z), real a ≥ 0, complex z, ν =0,1, 2,... |
S17DGF
|
Airy functions Ai(z) and Ai'(z), complex z |
S17DHF
|
Airy functions Bi(z) and Bi'(z), complex z |
S17DLF
|
Hankel functions Hν+a(j)(z), j=1,2, real a ≥ 0, complex z, ν =0,1,2,... |
S18ACF
|
Modified Bessel function K0 (x) |
S18ADF
|
Modified Bessel function K1 (x) |
S18AEF
|
Modified Bessel function I0 (x) |
S18AFF
|
Modified Bessel function I1(x) |
S18CCF
|
Modified Bessel function exK0(x) |
S18CDF
|
Modified Bessel function exK1(x) |
S18CEF
|
Modified Bessel function e-|x|I0(x) |
S18CFF
|
Modified Bessel function e-|x|I1(x) |
S18DCF
|
Modified Bessel functions Kν+a(z), real a ≥ 0, complex z, ν =0,1,2,... |
S18DEF
|
Modified Bessel functions Iν+a(z), real a ≥ 0, complex z, ν =0,1,2,... |
S19AAF
|
Kelvin function ber x |
S19ABF
|
Kelvin function bei x |
S19ACF
|
Kelvin function ker x |
S19ADF
|
Kelvin function kei x |
S20ACF
|
Fresnel integral S(x) |
S20ADF
|
Fresnel integral C(x) |
S21BAF
|
Degenerate symmetrised elliptic integral of 1st kind RC(x,y) |
S21BBF
|
Symmetrised elliptic integral of 1st kind RF(x,y,z) |
S21BCF
|
Symmetrised elliptic integral of 2nd kind RD(x,y,z) |
S21BDF
|
Symmetrised elliptic integral of 3rd kind RJ(x,y,z,r) |
S21CAF
|
Jacobian elliptic functions sn, cn and dn of real argument
|
S21CBF
|
Jacobian elliptic functions sn, cn and dn of complex argument
|
S21CCF
|
Jacobian theta functions θk (x,q) of real argument
|
S21DAF
|
General elliptic integral of 2nd kind F(z,k',a,b) of complex argument
|
S22AAF
|
Legendre functions of 1st kind Pnm (x) or Pnmx |
X01: Mathematical Constants
X02: Machine Constants
X03: Inner Products
X04: Input/Output Utilities
X05: Date and Time Utilities
|