Routine Name |
Purpose |
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 (DGETRF) |
F07AHF | Refined solution with error bounds of real system of linear equations, multiple right-hand sides |
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 (ZGETRF) |
F07AVF | Refined solution with error bounds of complex system of linear equations, multiple right-hand sides |
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 (DGBTRF) |
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 (ZGBTRF) |
F07BVF | Refined solution with error bounds of complex band system of linear equations, multiple right-hand sides |
F07CHF | Refined solution with error bounds of real tridiagonal system of linear equations, multiple right-hand sides |
F07CVF | Refined solution with error bounds of complex tridiagonal 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 (DPOTRF) |
F07FHF | Refined solution with error bounds of real symmetric positive definite system of linear equations, multiple right-hand sides |
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 (ZPOTRF) |
F07FVF | Refined solution with error bounds of complex Hermitian positive definite system of linear equations, multiple right-hand sides |
F07GEF | Solution of real symmetric positive definite system of linear equations, multiple right-hand sides, matrix already factorized by F07GDF (DPPTRF), packed storage |
F07GHF | Refined solution with error bounds of real symmetric positive definite system of linear equations, multiple right-hand sides, packed storage |
F07GSF | Solution of complex Hermitian positive definite system of linear equations, multiple right-hand sides, matrix already factorized by F07GRF (ZPPTRF), packed storage |
F07GVF | Refined solution with error bounds of complex Hermitian positive definite system of linear equations, multiple right-hand sides, packed storage |
F07HEF | Solution of real symmetric positive definite band system of linear equations, multiple right-hand sides, matrix already factorized by F07HDF (DPBTRF) |
F07HHF | Refined solution with error bounds of real symmetric positive definite band system of linear equations, multiple right-hand sides |
F07HSF | Solution of complex Hermitian positive definite band system of linear equations, multiple right-hand sides, matrix already factorized by F07HRF (ZPBTRF) |
F07HVF | Refined solution with error bounds of complex Hermitian positive definite band system of linear equations, multiple right-hand sides |
F07JHF | Refined solution with error bounds of real symmetric positive definite tridiagonal system of linear equations, multiple right-hand sides |
F07JVF | Refined solution with error bounds of complex Hermitian positive definite tridiagonal system of linear equations, multiple right-hand sides |
F07MHF | Refined solution with error bounds of real symmetric indefinite system of linear equations, multiple right-hand sides |
F07MVF | Refined solution with error bounds of complex Hermitian indefinite system of linear equations, multiple right-hand sides |
F07NVF | Refined solution with error bounds of complex symmetric system of linear equations, multiple right-hand sides |
F07PHF | Refined solution with error bounds of real symmetric indefinite system of linear equations, multiple right-hand sides, packed storage |
F07PVF | Refined solution with error bounds of complex Hermitian indefinite system of linear equations, multiple right-hand sides, packed storage |
F07QVF | Refined solution with error bounds of complex symmetric system of linear equations, multiple right-hand sides, packed storage |
F07THF | Error bounds for solution of real triangular system of linear equations, multiple right-hand sides |
F07TVF | Error bounds for solution of complex triangular system of linear equations, multiple right-hand sides |
F07UEF | Solution of real triangular system of linear equations, multiple right-hand sides, packed storage |
F07UHF | Error bounds for solution of real triangular system of linear equations, multiple right-hand sides, packed storage |
F07USF | Solution of complex triangular system of linear equations, multiple right-hand sides, packed storage |
F07UVF | Error bounds for solution of complex triangular system of linear equations, multiple right-hand sides, packed storage |
F07VEF | Solution of real band triangular system of linear equations, multiple right-hand sides |
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 |
F07VVF | Error bounds for solution of complex band triangular system of linear equations, multiple right-hand sides |
F08AEF | QR factorization of real general rectangular matrix |
F08AFF | Form all or part of orthogonal Q from QR factorization determined by F08AEF (DGEQRF), F08BEF (DGEQPF) or F08BFF (DGEQP3) |
F08AGF | Apply orthogonal transformation determined by F08AEF (DGEQRF), F08BEF (DGEQPF) or F08BFF (DGEQP3) |
F08ASF | QR factorization of complex general rectangular matrix |
F08ATF | Form all or part of unitary Q from QR factorization determined by F08ASF (ZGEQRF), F08BSF (ZGEQPF) or F08BTF (ZGEQP3) |
F08AUF | Apply unitary transformation determined by F08ASF (ZGEQRF), F08BSF (ZGEQPF) or F08BTF (ZGEQP3) |
F08FEF | Orthogonal reduction of real symmetric matrix to symmetric tridiagonal form |
F08FFF | Generate orthogonal transformation matrix from reduction to tridiagonal form determined by F08FEF (DSYTRD) |
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 (ZHETRD) |
F08GFF | Generate orthogonal transformation matrix from reduction to tridiagonal form determined by F08GEF (DSPTRD) |
F08GTF | Generate unitary transformation matrix from reduction to tridiagonal form determined by F08GSF (ZHPTRD) |
F08HEF | Orthogonal reduction of real symmetric band matrix to symmetric tridiagonal form |
F08HSF | Unitary reduction of complex Hermitian band matrix to real symmetric tridiagonal form |
F08JEF | All eigenvalues and eigenvectors of real symmetric tridiagonal matrix, reduced from real symmetric matrix using the implicit QL or QR algorithm |
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 the implicit QL or QR algorithm |
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 |
F08KSF | Unitary reduction of complex general rectangular matrix to bidiagonal form |
F08MEF | SVD of real bidiagonal matrix reduced from real general matrix |
F08MSF | SVD of real bidiagonal matrix reduced from complex general matrix |
F08PKF | Selected right and/or left eigenvectors of real upper Hessenberg matrix by inverse iteration |
F08PXF | Selected right and/or left eigenvectors of complex upper Hessenberg matrix by inverse iteration |
F08TAF | Computes all the eigenvalues, and optionally, the eigenvectors of a real generalized symmetric-definite eigenproblem, packed storage |
F08TBF | Computes selected eigenvalues, and optionally, the eigenvectors of a real generalized symmetric-definite eigenproblem, packed storage |
F08TCF | Computes all the eigenvalues, and optionally, the eigenvectors of a real generalized symmetric-definite eigenproblem, packed storage (divide-and-conquer) |
F08TNF | Computes all the eigenvalues, and optionally, the eigenvectors of a complex generalized Hermitian-definite eigenproblem, packed storage |
F08TPF | Computes selected eigenvalues, and optionally, the eigenvectors of a complex generalized Hermitian-definite eigenproblem, packed storage |
F08TQF | Computes selected eigenvalues, and optionally, the eigenvectors of a complex generalized Hermitian-definite eigenproblem, packed storage (divide-and-conquer) |
Routine Name |
Purpose |
C02AKF | All zeros of real cubic equation |
C02ALF | All zeros of real quartic equation |
C02AMF | All zeros of complex cubic equation |
C02ANF | All zeros of complex quartic equation |
C05QBF | Solution of a system of nonlinear equations using function values only (easy-to-use) |
C05QCF | Solution of a system of nonlinear equations using function values only (comprehensive) |
C05QDF | Solution of a system of nonlinear equations using function values only (reverse communication) |
C05RBF | Solution of a system of nonlinear equations using first derivatives (easy-to-use) |
C05RCF | Solution of a system of nonlinear equations using first derivatives (comprehensive) |
C05RDF | Solution of a system of nonlinear equations using first derivatives (reverse communication) |
D02AGF | Ordinary differential equations, boundary value problem, shooting and matching technique, allowing interior matching point, general parameters to be determined |
D02HAF | Ordinary differential equations, boundary value problem, shooting and matching, boundary values to be determined |
D02HBF | Ordinary differential equations, boundary value problem, shooting and matching, general parameters to be determined |
D02NEF | Implicit ordinary differential equations/DAEs, initial value problem, DASSL method integrator |
D02SAF | Ordinary differential equations, boundary value problem, shooting and matching technique, subject to extra algebraic equations, general parameters to be determined |
D02TKF | Ordinary differential equations, general nonlinear boundary value problem, collocation technique |
D02UEF | Solve linear constant coefficient boundary value problem on Chebyshev grid, Integral formulation |
D03NCF | Finite difference solution of the Black–Scholes equations |
D05BDF | Nonlinear convolution Volterra–Abel equation, second kind, weakly singular |
D05BEF | Nonlinear convolution Volterra–Abel equation, first kind, weakly singular |
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) |
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) |
E04NCF | Convex QP problem or linearly-constrained linear least squares problem (dense) |
E04UCF | Minimum, function of several variables, sequential QP method, nonlinear constraints, using function values and optionally first derivatives (comprehensive) |
E04UFF | Minimum, function of several variables, sequential QP method, nonlinear constraints, using function values and optionally first derivatives (reverse communication, comprehensive) |
E04USF | Minimum of a sum of squares, nonlinear constraints, sequential QP method, using function values and optionally first derivatives (comprehensive) |
F01ABF | Inverse of real symmetric positive definite matrix using iterative refinement |
F01ADF | Inverse of real symmetric positive definite matrix |
F01ECF | Real matrix exponential |
F01EDF | Real symmetric matrix exponential |
F01EFF | Function of a real symmetric matrix |
F01FCF | Complex matrix exponential |
F01FDF | Complex Hermitian matrix exponential |
F01FFF | Function of a complex Hermitian matrix |
F02ECF | Selected eigenvalues and eigenvectors of real nonsymmetric matrix (Black Box) |
F02FJF | Selected eigenvalues and eigenvectors of sparse symmetric eigenproblem (Black Box) |
F02GCF | Selected eigenvalues and eigenvectors of complex nonsymmetric matrix (Black Box) |
F02WDF | QR factorization, possibly followed by SVD |
F02WGF | Computes leading terms in the singular value decomposition of a real general matrix; also computes corresponding left and right singular vectors |
F02WUF | SVD of real upper triangular matrix (Black Box) |
F02XUF | SVD of complex upper triangular matrix (Black Box) |
F04ABF | Solution of real symmetric positive definite simultaneous linear equations with multiple right-hand sides using iterative refinement (Black Box) |
F04ASF | Solution of real symmetric positive definite simultaneous linear equations, one right-hand side using iterative refinement (Black Box) |
F04BAF | Computes the solution and error-bound to a real system of linear equations |
F04BBF | Computes the solution and error-bound to a real banded system of linear equations |
F04BDF | Computes the solution and error-bound to a real symmetric positive definite system of linear equations |
F04BEF | Computes the solution and error-bound to a real symmetric positive definite system of linear equations, packed storage |
F04BFF | Computes the solution and error-bound to a real symmetric positive definite banded system of linear equations |
F04CAF | Computes the solution and error-bound to a complex system of linear equations |
F04CBF | Computes the solution and error-bound to a complex banded system of linear equations |
F04CDF | Computes the solution and error-bound to a complex Hermitian positive definite system of linear equations |
F04CEF | Computes the solution and error-bound to a complex Hermitian positive definite system of linear equations, packed storage |
F04CFF | Computes the solution and error-bound to a complex Hermitian positive definite banded system of linear equations |
F04JGF | Least squares (if rank = n) or minimal least squares (if rank < n) solution of m real equations in n unknowns, m ≥ n |
F07AAF | Computes the solution to a real system of linear equations |
F07ABF | Uses the LU factorization to compute the solution, error-bound and condition estimate for a real system of linear equations |
F07ACF | Mixed precision real system solver |
F07ANF | Computes the solution to a complex system of linear equations |
F07APF | Uses the LU factorization to compute the solution, error-bound and condition estimate for a complex system of linear equations |
F07AQF | Mixed precision complex system solver |
F07BAF | Computes the solution to a real banded system of linear equations |
F07BBF | Uses the LU factorization to compute the solution, error-bound and condition estimate for a real banded system of linear equations |
F07BNF | Computes the solution to a complex banded system of linear equations |
F07BPF | Uses the LU factorization to compute the solution, error-bound and condition estimate for a complex banded system of linear equations |
F07CBF | Uses the LU factorization to compute the solution, error-bound and condition estimate for a real tridiagonal system of linear equations |
F07CPF | Uses the LU factorization to compute the solution, error-bound and condition estimate for a complex tridiagonal system of linear equations |
F07FAF | Computes the solution to a real symmetric positive definite system of linear equations |
F07FBF | Uses the Cholesky factorization to compute the solution, error-bound and condition estimate for a real symmetric positive definite system of linear equations |
F07FCF | Uses the Cholesky factorization to compute the solution for a real symmetric positive definite system of linear equations |
F07FNF | Computes the solution to a complex Hermitian positive definite system of linear equations |
F07FPF | Uses the Cholesky factorization to compute the solution, error-bound and condition estimate for a complex Hermitian positive definite system of linear equations |
F07FQF | Uses the Cholesky factorization to compute the solution for a complex Hermitian positive definite system of linear equations |
F07GAF | Computes the solution to a real symmetric positive definite system of linear equations, packed storage |
F07GBF | Uses the Cholesky factorization to compute the solution, error-bound and condition estimate for a real symmetric positive definite system of linear equations, packed storage |
F07GNF | Computes the solution to a complex Hermitian positive definite system of linear equations, packed storage |
F07GPF | Uses the Cholesky factorization to compute the solution, error-bound and condition estimate for a complex Hermitian positive definite system of linear equations, packed storage |
F07HAF | Computes the solution to a real symmetric positive definite banded system of linear equations |
F07HBF | Uses the Cholesky factorization to compute the solution, error-bound and condition estimate for a real symmetric positive definite banded system of linear equations |
F07HNF | Computes the solution to a complex Hermitian positive definite banded system of linear equations |
F07HPF | Uses the Cholesky factorization to compute the solution, error-bound and condition estimate for a complex Hermitian positive definite banded system of linear equations |
F07JBF | Uses the modified Cholesky factorization to compute the solution, error-bound and condition estimate for a real symmetric positive definite tridiagonal system of linear equations |
F07JPF | Uses the modified Cholesky factorization to compute the solution, error-bound and condition estimate for a complex Hermitian positive definite tridiagonal system of linear equations |
F07MBF | Uses the diagonal pivoting factorization to compute the solution to a real symmetric system of linear equations |
F07MPF | Uses the diagonal pivoting factorization to compute the solution to a complex Hermitian system of linear equations |
F07NPF | Uses the diagonal pivoting factorization to compute the solution to a complex symmetric system of linear equations |
F07PBF | Uses the diagonal pivoting factorization to compute the solution to a real symmetric system of linear equations, packed storage |
F07PPF | Uses the diagonal pivoting factorization to compute the solution to a complex Hermitian system of linear equations, packed storage |
F07QPF | Uses the diagonal pivoting factorization to compute the solution to a complex symmetric system of linear equations, packed storage |
F07WDF | Cholesky factorization of real symmetric positive definite matrix, Rectangular Full Packed format |
F07WRF | Cholesky factorization of complex Hermitian positive definite matrix, Rectangular Full Packed format |
F08AAF | Solves an overdetermined or underdetermined real linear system |
F08ANF | Solves an overdetermined or underdetermined complex linear system |
F08BAF | Computes the minimum-norm solution to a real linear least squares problem |
F08BFF | QR factorization of real general rectangular matrix with column pivoting, using BLAS-3 |
F08BNF | Computes the minimum-norm solution to a complex linear least squares problem |
F08BTF | QR factorization of complex general rectangular matrix with column pivoting, using BLAS-3 |
F08FAF | Computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix |
F08FBF | Computes selected eigenvalues and, optionally, eigenvectors of a real symmetric matrix |
F08FCF | Computes all eigenvalues and, optionally, all eigenvectors of real symmetric matrix (divide-and-conquer) |
F08FDF | Computes selected eigenvalues and, optionally, eigenvectors of a real symmetric matrix (Relatively Robust Representations) |
F08FGF | Apply orthogonal transformation determined by F08FEF (DSYTRD) |
F08FNF | Computes all eigenvalues and, optionally, eigenvectors of a complex Hermitian matrix |
F08FPF | Computes selected eigenvalues and, optionally, eigenvectors of a complex Hermitian matrix |
F08FQF | Computes all eigenvalues and, optionally, all eigenvectors of complex Hermitian matrix (divide-and-conquer) |
F08FRF | Computes selected eigenvalues and, optionally, eigenvectors of a complex Hermitian matrix (Relatively Robust Representations) |
F08FUF | Apply unitary transformation matrix determined by F08FSF (ZHETRD) |
F08GAF | Computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix, packed storage |
F08GBF | Computes selected eigenvalues and, optionally, eigenvectors of a real symmetric matrix, packed storage |
F08GCF | Computes all eigenvalues and, optionally, all eigenvectors of real symmetric matrix, packed storage (divide-and-conquer) |
F08GNF | Computes all eigenvalues and, optionally, eigenvectors of a complex Hermitian matrix, packed storage |
F08GPF | Computes selected eigenvalues and, optionally, eigenvectors of a complex Hermitian matrix, packed storage |
F08GQF | Computes all eigenvalues and, optionally, all eigenvectors of complex Hermitian matrix, packed storage (divide-and-conquer) |
F08HAF | Computes all eigenvalues and, optionally, eigenvectors of a real symmetric band matrix |
F08HBF | Computes selected eigenvalues and, optionally, eigenvectors of a real symmetric band matrix |
F08HCF | Computes all eigenvalues and, optionally, all eigenvectors of real symmetric band matrix (divide-and-conquer) |
F08HNF | Computes all eigenvalues and, optionally, eigenvectors of a complex Hermitian band matrix |
F08HPF | Computes selected eigenvalues and, optionally, eigenvectors of a complex Hermitian band matrix |
F08HQF | Computes all eigenvalues and, optionally, all eigenvectors of complex Hermitian band matrix (divide-and-conquer) |
F08JAF | Computes all eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix |
F08JBF | Computes selected eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix |
F08JCF | Computes all eigenvalues and, optionally, all eigenvectors of real symmetric tridiagonal matrix (divide-and-conquer) |
F08JDF | Computes selected eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix (Relatively Robust Representations) |
F08JGF | Computes all eigenvalues and eigenvectors of real symmetric positive definite tridiagonal matrix, reduced from real symmetric positive definite matrix |
F08JHF | Computes all eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix or a matrix reduced to this form (divide-and-conquer) |
F08JLF | Computes all eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix or a symmetric matrix reduced to this form (Relatively Robust Representations) |
F08JUF | Computes all eigenvalues and eigenvectors of real symmetric positive definite tridiagonal matrix, reduced from complex Hermitian positive definite matrix |
F08JVF | Computes all eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix or a complex Hermitian matrix reduced to this form (divide-and-conquer) |
F08JYF | Computes all eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix or a complex Hermitian matrix reduced to this form (Relatively Robust Representations) |
F08KAF | Computes the minimum-norm solution to a real linear least squares problem using singular value decomposition |
F08KBF | Computes the singular value decomposition of a real matrix, optionally computing the left and/or right singular vectors |
F08KCF | Computes the minimum-norm solution to a real linear least squares problem using singular value decomposition (divide-and-conquer) |
F08KDF | Computes the singular value decomposition of a real matrix, optionally computing the left and/or right singular vectors (divide-and-conquer) |
F08KFF | Generate orthogonal transformation matrices from reduction to bidiagonal form determined by F08KEF (DGEBRD) |
F08KGF | Apply orthogonal transformations from reduction to bidiagonal form determined by F08KEF (DGEBRD) |
F08KHF | Computes the singular value decomposition of a real matrix, optionally computing the left and/or right singular vectors (preconditioned Jacobi) |
F08KNF | Computes the minimum-norm solution to a complex linear least squares problem using singular value decomposition |
F08KPF | Computes the singular value decomposition of a complex matrix, optionally computing the left and/or right singular vectors |
F08KQF | Computes the minimum-norm solution to a complex linear least squares problem using singular value decomposition (divide-and-conquer) |
F08KRF | Computes the singular value decomposition of a complex matrix, optionally computing the left and/or right singular vectors (divide-and-conquer) |
F08KTF | Generate unitary transformation matrices from reduction to bidiagonal form determined by F08KSF (ZGEBRD) |
F08KUF | Apply unitary transformations from reduction to bidiagonal form determined by F08KSF (ZGEBRD) |
F08MDF | Computes the singular value decomposition of a real bidiagonal matrix, optionally computing the singular vectors (divide-and-conquer) |
F08NAF | Computes all eigenvalues and, optionally, left and/or right eigenvectors of a real nonsymmetric matrix |
F08NBF | Computes all eigenvalues and, optionally, left and/or right eigenvectors of a real nonsymmetric matrix; also, optionally, the balancing transformation, the reciprocal condition numbers for the eigenvalues and for the right eigenvectors |
F08NFF | Generate orthogonal transformation matrix from reduction to Hessenberg form determined by F08NEF (DGEHRD) |
F08NGF | Apply orthogonal transformation matrix from reduction to Hessenberg form determined by F08NEF (DGEHRD) |
F08NNF | Computes all eigenvalues and, optionally, left and/or right eigenvectors of a complex nonsymmetric matrix |
F08NPF | Computes all eigenvalues and, optionally, left and/or right eigenvectors of a complex nonsymmetric matrix; also, optionally, the balancing transformation, the reciprocal condition numbers for the eigenvalues and for the right eigenvectors |
F08NTF | Generate unitary transformation matrix from reduction to Hessenberg form determined by F08NSF (ZGEHRD) |
F08NUF | Apply unitary transformation matrix from reduction to Hessenberg form determined by F08NSF (ZGEHRD) |
F08PAF | Computes for real square nonsymmetric matrix, the eigenvalues, the real Schur form, and, optionally, the matrix of Schur vectors |
F08PBF | Computes for real square nonsymmetric matrix, the eigenvalues, the real Schur form, and, optionally, the matrix of Schur vectors; also, optionally, computes reciprocal condition numbers for selected eigenvalues |
F08PEF | Computes the eigenvalues and Schur factorization of real upper Hessenberg matrix reduced from real general matrix |
F08PNF | Computes for complex square nonsymmetric matrix, the eigenvalues, the Schur form, and, optionally, the matrix of Schur vectors |
F08PPF | Computes for real square nonsymmetric matrix, the eigenvalues, the Schur form, and, optionally, the matrix of Schur vectors; also, optionally, computes reciprocal condition numbers for selected eigenvalues |
F08PSF | Computes the eigenvalues and Schur factorization of complex upper Hessenberg matrix reduced from complex general matrix |
F08SAF | Computes all the eigenvalues, and optionally, the eigenvectors of a real generalized symmetric-definite eigenproblem |
F08SBF | Computes selected eigenvalues, and optionally, the eigenvectors of a real generalized symmetric-definite eigenproblem |
F08SCF | Computes all the eigenvalues, and optionally, the eigenvectors of a real generalized symmetric-definite eigenproblem (divide-and-conquer) |
F08SNF | Computes all the eigenvalues, and optionally, the eigenvectors of a complex generalized Hermitian-definite eigenproblem |
F08SPF | Computes selected eigenvalues, and optionally, the eigenvectors of a complex generalized Hermitian-definite eigenproblem |
F08SQF | Computes all the eigenvalues, and optionally, the eigenvectors of a complex generalized Hermitian-definite eigenproblem (divide-and-conquer) |
F08UAF | Computes all the eigenvalues, and optionally, the eigenvectors of a real banded generalized symmetric-definite eigenproblem |
F08UBF | Computes selected eigenvalues, and optionally, the eigenvectors of a real banded generalized symmetric-definite eigenproblem |
F08UCF | Computes all the eigenvalues, and optionally, the eigenvectors of a real banded generalized symmetric-definite eigenproblem (divide-and-conquer) |
F08UNF | Computes all the eigenvalues, and optionally, the eigenvectors of a complex banded generalized Hermitian-definite eigenproblem |
F08UPF | Computes selected eigenvalues, and optionally, the eigenvectors of a complex banded generalized Hermitian-definite eigenproblem |
F08UQF | Computes all the eigenvalues, and optionally, the eigenvectors of a complex banded generalized Hermitian-definite eigenproblem (divide-and-conquer) |
F08WAF | Computes, for a real nonsymmetric matrix pair, the generalized eigenvalues, and optionally, the left and/or right generalized eigenvectors |
F08WBF | Computes, for a real nonsymmetric matrix pair, the generalized eigenvalues, and optionally, the left and/or right generalized eigenvectors; also, optionally, the balancing transformation, the reciprocal condition numbers for the eigenvalues and for the right eigenvectors |
F08WNF | Computes, for a complex nonsymmetric matrix pair, the generalized eigenvalues, and optionally, the left and/or right generalized eigenvectors |
F08WPF | Computes, for a complex nonsymmetric matrix pair, the generalized eigenvalues, and optionally, the left and/or right generalized eigenvectors; also, optionally, the balancing transformation, the reciprocal condition numbers for the eigenvalues and for the right eigenvectors |
F08XAF | Computes, for a real nonsymmetric matrix pair, the generalized eigenvalues, the generalized real Schur form and, optionally, the left and/or right matrices of Schur vectors |
F08XBF | Computes, for a real nonsymmetric matrix pair, the generalized eigenvalues, the generalized real Schur form and, optionally, the left and/or right matrices of Schur vectors; also, optionally, computes reciprocal condition numbers for selected eigenvalues |
F08XNF | Computes, for a complex nonsymmetric matrix pair, the generalized eigenvalues, the generalized complex Schur form and, optionally, the left and/or right matrices of Schur vectors |
F08XPF | Computes, for a complex nonsymmetric matrix pair, the generalized eigenvalues, the generalized complex Schur form and, optionally, the left and/or right matrices of Schur vectors; also, optionally, computes reciprocal condition numbers for selected eigenvalues |
F08ZAF | Solves the real linear equality-constrained least squares (LSE) problem |
F08ZBF | Solves a real general Gauss–Markov linear model (GLM) problem |
F08ZEF | Computes a generalized QR factorization of a real matrix pair |
F08ZFF | Computes a generalized RQ factorization of a real matrix pair |
F08ZNF | Solves the complex linear equality-constrained least squares (LSE) problem |
F08ZPF | Solves a complex general Gauss–Markov linear model (GLM) problem |
F08ZSF | Computes a generalized QR factorization of a complex matrix pair |
F08ZTF | Computes a generalized RQ factorization of a complex matrix pair |
F12FCF | Selected eigenvalues and, optionally, eigenvectors of a real symmetric sparse eigenproblem, postprocessing for F12FBF |
F12FGF | Selected eigenvalues and, optionally, eigenvectors of a real symmetric banded eigenproblem, driver |
G01HBF | Computes probabilities for the multivariate Normal distribution |
G02ABF | Computes the nearest correlation matrix to a real square matrix, augmented G02AAF to incorporate weights and bounds |
G02AEF | Computes the nearest correlation matrix with k-factor structure to a real square matrix |
G02BYF | Computes partial correlation/variance-covariance matrix from correlation/variance-covariance matrix computed by G02BXF |
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 |
G02DDF | Estimates of linear parameters and general linear regression model from updated model |
G02EAF | Computes residual sums of squares for all possible linear regressions for a set of independent variables |
G02EEF | Fits a linear regression model by forward selection |
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 |
G02HAF | Robust regression, standard M-estimates |
G02HDF | Robust regression, compute regression with user-supplied functions and weights |
G02HFF | Robust regression, variance-covariance matrix following G02HDF |
G02JAF | Linear mixed effects regression using Restricted Maximum Likelihood (REML) |
G02JBF | Linear mixed effects regression using Maximum Likelihood (ML) |
G02KAF | Ridge regression, optimizing a ridge regression parameter |
G02KBF | Ridge regression using a number of supplied ridge regression parameters |
G02LAF | Partial least squares (PLS) regression using singular value decomposition |
G02LCF | PLS parameter estimates following partial least squares regression by G02LAF or G02LBF |
G02QFF | Quantile linear regression, simple interface, independent, identically distributed (IID) errors |
G02QGF | Quantile linear regression, comprehensive interface |
G03AAF | Performs principal component analysis |
G03ACF | Performs canonical variate analysis |
G03ADF | Performs canonical correlation analysis |
G03BAF | Computes orthogonal rotations for loading matrix, generalized orthomax criterion |
G03BCF | Computes Procrustes rotations |
G03BDF | ProMax rotations |
G03DAF | Computes test statistic for equality of within-group covariance matrices and matrices for discriminant analysis |
G03FAF | Performs principal coordinate analysis, classical metric scaling |
G04BBF | Analysis of variance, randomized block or completely randomized design, treatment means and standard errors |
G04BCF | Analysis of variance, general row and column design, treatment means and standard errors |
G05PJF | Generates a realization of a multivariate time series from a VARMA model |
G08RAF | Regression using ranks, uncensored data |
G08RBF | Regression using ranks, right-censored data |
G11CAF | Returns parameter estimates for the conditional analysis of stratified data |
G11SAF | Contingency table, latent variable model for binary data |
G12ABF | Computes rank statistics for comparing survival curves |
G12BAF | Fits Cox's proportional hazard model |
G13AEF | Univariate time series, estimation, seasonal ARIMA model (comprehensive) |
G13AFF | Univariate time series, estimation, seasonal ARIMA model (easy-to-use) |
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 |
G13BAF | Multivariate time series, filtering (pre-whitening) by an ARIMA model |
G13BBF | Multivariate time series, filtering by a transfer function model |
G13BDF | Multivariate time series, preliminary estimation of transfer function model |
G13BEF | Multivariate time series, estimation of multi-input model |
G13BJF | Multivariate time series, state set and forecasts from fully specified multi-input model |
G13DBF | Multivariate time series, multiple squared partial autocorrelations |
G13DDF | Multivariate time series, estimation of VARMA model |
G13DJF | Multivariate time series, forecasts and their standard errors |
G13DNF | Multivariate time series, sample partial lag correlation matrices, χ^{2} statistics and significance levels |
G13DPF | Multivariate time series, partial autoregression matrices |
G13DSF | Multivariate time series, diagnostic checking of residuals, following G13DDF |
G13DXF | Calculates the zeros of a vector autoregressive (or moving average) operator |
G13FAF | Univariate time series, parameter estimation for either a symmetric GARCH process or a GARCH process with asymmetry of the form (ε_{t − 1} + γ)^{2} |
G13FCF | Univariate time series, parameter estimation for a GARCH process with asymmetry of the form (|ε_{t − 1}| + γε_{t − 1})^{2} |
G13FEF | Univariate time series, parameter estimation for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process |
G13FGF | Univariate time series, parameter estimation for an exponential GARCH (EGARCH) process |
Routine Name |
Purpose |
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 |
C06HAF | Discrete sine transform |
C06HBF | Discrete cosine transform |
C06HCF | Discrete quarter-wave sine transform |
C06HDF | Discrete quarter-wave cosine transform |
C06PAF | Single one-dimensional real and Hermitian complex discrete Fourier transform, using complex storage format for Hermitian sequences |
C06PFF | One-dimensional complex discrete Fourier transform of multidimensional data (using complex data type) |
C06PJF | Multidimensional complex discrete Fourier transform of multidimensional 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 row ordered complex storage format for Hermitian sequences |
C06PQF | Multiple one-dimensional real and Hermitian complex discrete Fourier transforms, using column ordered complex storage format for Hermitian sequences |
C06PRF | Multiple one-dimensional complex discrete Fourier transforms using complex data type |
C06PSF | Multiple one-dimensional complex discrete Fourier transforms using complex data type and sequences stored as columns |
C06PUF | Two-dimensional complex discrete Fourier transform, complex data type |
C06PXF | Three-dimensional complex discrete Fourier transform, complex data type |
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) |
C09EAF | Two-dimensional discrete wavelet transform |
C09EBF | Two-dimensional inverse discrete wavelet transform |
C09ECF | Two-dimensional multi-level discrete wavelet transform |
C09EDF | Two-dimensional inverse multi-level discrete wavelet transform |
D01DAF | Two-dimensional quadrature, finite region |
D01FCF | Multidimensional adaptive quadrature over hyper-rectangle |
D01GAF | One-dimensional quadrature, integration of function defined by data values, Gill–Miller method |
D03FAF | Elliptic PDE, Helmholtz equation, three-dimensional Cartesian coordinates |
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 |
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 |
E01TKF | Interpolating functions, modified Shepard's method, four variables |
E01TLF | Interpolated values, evaluate interpolant computed by E01TKF, function and first derivatives, four variables |
E01TMF | Interpolating functions, modified Shepard's method, five variables |
E01TNF | Interpolated values, evaluate interpolant computed by E01TMF, function and first derivatives, five variables |
E02CAF | Least squares surface fit by polynomials, data on lines parallel to one independent coordinate axis |
E02CBF | Evaluation of fitted polynomial in two variables |
E02DFF | Evaluation of fitted bicubic spline at a mesh of points |
E05SAF | Global optimization using particle swarm algorithm (PSO), bound constraints only |
E05SBF | Global optimization using particle swarm algorithm (PSO), comprehensive |
F01CTF | Sum or difference of two real matrices, optional scaling and transposition |
F01CWF | Sum or difference of two complex matrices, optional scaling and transposition |
F05AAF | Gram–Schmidt orthogonalisation of n vectors of order m |
F11BEF | Real sparse nonsymmetric linear systems, preconditioned RGMRES, CGS, Bi-CGSTAB or TFQMR method |
F11BSF | Complex sparse non-Hermitian linear systems, preconditioned RGMRES, CGS, Bi-CGSTAB or TFQMR method |
F11GEF | Real sparse symmetric linear systems, preconditioned conjugate gradient or Lanczos method or the MINRES algorithm |
F11GSF | Complex sparse Hermitian linear systems, preconditioned conjugate gradient or Lanczos |
F11MEF | LU factorization of real sparse matrix |
F11MFF | Solution of real sparse simultaneous linear equations (coefficient matrix already factorized) |
F11MHF | Refined solution with error bounds of real system of linear equations, multiple right-hand sides |
F11MKF | Real sparse nonsymmetric matrix-matrix multiply, compressed column storage |
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 |
F12ABF | Selected eigenvalues and, optionally, eigenvectors of a real nonsymmetric sparse eigenproblem, reverse communication |
F12AGF | Selected eigenvalues and, optionally, eigenvectors of a real nonsymmetric banded eigenproblem, driver |
F12APF | Selected eigenvalues and, optionally, eigenvectors of a complex sparse eigenproblem, reverse communication |
F12FBF | Selected eigenvalues and, optionally, eigenvectors of a real symmetric sparse eigenproblem, reverse communication |
G02AAF | Computes the nearest correlation matrix to a real square matrix, using the method of Qi and Sun |
G02BAF | Pearson product-moment correlation coefficients, all variables, no missing values |
G02BDF | Correlation-like coefficients (about zero), all variables, no 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 |
G02JDF | Hierarchical mixed effects regression using Restricted Maximum Likelihood (REML) |
G02JEF | Hierarchical mixed effects regression using Maximum Likelihood (ML) |
G03CAF | Computes maximum likelihood estimates of the parameters of a factor analysis model, factor loadings, communalities and residual correlations |
G03EAF | Computes distance matrix |
G03ECF | Hierarchical cluster analysis |
G05RCF | Generates a matrix of pseudorandom numbers from a Student's t-copula |
G05RDF | Generates a matrix of pseudorandom numbers from a Gaussian copula |
G05REF | Generates a matrix of pseudorandom numbers from a bivariate Clayton/Cook–Johnson copula |
G05RFF | Generates a matrix of pseudorandom numbers from a bivariate Frank copula |
G05RGF | Generates a matrix of pseudorandom numbers from a bivariate Plackett copula |
G05RHF | Generates a matrix of pseudorandom numbers from a multivariate Clayton/Cook–Johnson copula |
G05RJF | Generates a matrix of pseudorandom numbers from a multivariate Frank copula |
G05RKF | Generates a matrix of pseudorandom numbers from a Gumbel–Hougaard copula |
G05RYF | Generates a matrix of pseudorandom numbers from a multivariate Student's t-distribution |
G05SAF | Generates a vector of pseudorandom numbers from a uniform distribution over (0,1] |
G05SBF | Generates a vector of pseudorandom numbers from a beta distribution |
G05SCF | Generates a vector of pseudorandom numbers from a Cauchy distribution |
G05SDF | Generates a vector of pseudorandom numbers from a χ^{2} distribution |
G05SEF | Generates a vector of pseudorandom numbers from a Dirichlet distribution |
G05SFF | Generates a vector of pseudorandom numbers from an exponential distribution |
G05SGF | Generates a vector of pseudorandom numbers from an exponential mix distribution |
G05SHF | Generates a vector of pseudorandom numbers from an F-distribution |
G05SJF | Generates a vector of pseudorandom numbers from a gamma distribution |
G05SKF | Generates a vector of pseudorandom numbers from a Normal distribution |
G05SLF | Generates a vector of pseudorandom numbers from a logistic distribution |
G05SMF | Generates a vector of pseudorandom numbers from a log-normal distribution |
G05SNF | Generates a vector of pseudorandom numbers from a Student's t-distribution |
G05SPF | Generates a vector of pseudorandom numbers from a triangular distribution |
G05SQF | Generates a vector of pseudorandom numbers from a uniform distribution over [a,b] |
G05SRF | Generates a vector of pseudorandom numbers from a von Mises distribution |
G05SSF | Generates a vector of pseudorandom numbers from a Weibull distribution |
G05YJF | Generates a Normal quasi-random number sequence |
G05YKF | Generates a log-normal quasi-random number sequence |
G05YMF | Generates a uniform quasi-random number sequence |
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 |
M01CAF | Sort a vector, real numbers |
M01CBF | Sort a vector, integer numbers |
M01CCF | Sort a vector, character data |
S30AAF | Black–Scholes–Merton option pricing formula |
S30ABF | Black–Scholes–Merton option pricing formula with Greeks |
S30BAF | Floating-strike lookback option pricing formula |
S30BBF | Floating-strike lookback option pricing formula with Greeks |
S30CAF | Binary option: cash-or-nothing pricing formula |
S30CBF | Binary option: cash-or-nothing pricing formula with Greeks |
S30CCF | Binary option: asset-or-nothing pricing formula |
S30CDF | Binary option: asset-or-nothing pricing formula with Greeks |
S30FAF | Standard barrier option pricing formula |
S30JAF | Jump-diffusion, Merton's model, option pricing formula |
S30JBF | Jump-diffusion, Merton's model, option pricing formula with Greeks |
S30NAF | Heston's model option pricing formula |
S30NBF | Heston's model option pricing formula with Greeks |
S30QCF | American option: Bjerksund and Stensland pricing formula |
S30SAF | Asian option: geometric continuous average rate pricing formula |
S30SBF | Asian option: geometric continuous average rate pricing formula with Greeks |
Routine Name |
Purpose |
C05QSF | Solution of a sparse system of nonlinear equations using function values only (easy-to-use) |
D01GBF | Multidimensional quadrature over hyper-rectangle, Monte–Carlo method |
D01GCF | Multidimensional quadrature, general product region, number-theoretic method |
D01GDF | Multidimensional quadrature, general product region, number-theoretic method, variant of D01GCF efficient on vector machines |
D01PAF | Multidimensional quadrature over an n-simplex |
D02EJF | Ordinary differential equations, stiff initial value problem, backward differentiation formulae method, until function of solution is zero, intermediate output (simple driver) |
D02NBF | Explicit ordinary differential equations, stiff initial value problem, full Jacobian (comprehensive) |
D02NCF | Explicit ordinary differential equations, stiff initial value problem, banded Jacobian (comprehensive) |
D02NDF | Explicit ordinary differential equations, stiff initial value problem, sparse Jacobian (comprehensive) |
D02NGF | Implicit/algebraic ordinary differential equations, stiff initial value problem, full Jacobian (comprehensive) |
D02NHF | Implicit/algebraic ordinary differential equations, stiff initial value problem, banded Jacobian (comprehensive) |
D02NJF | Implicit/algebraic ordinary differential equations, stiff initial value problem, sparse Jacobian (comprehensive) |
D02NMF | Explicit ordinary differential equations, stiff initial value problem (reverse communication, comprehensive) |
D02NNF | Implicit/algebraic ordinary differential equations, stiff initial value problem (reverse communication, comprehensive) |
D02UAF | Coefficients of Chebyshev interpolating polynomial from function values on Chebyshev grid |
D02UBF | Function or low-order-derivative values on Chebyshev grid from coefficients of Chebyshev interpolating polynomial |
D03PCF | General system of parabolic PDEs, method of lines, finite differences, one space variable |
D03PDF | General system of parabolic PDEs, method of lines, Chebyshev C^{0} collocation, one space variable |
D03PEF | General system of first-order PDEs, method of lines, Keller box discretization, 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 C^{0} collocation, one space variable |
D03PKF | General system of first-order PDEs, coupled DAEs, method of lines, Keller box discretization, 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 discretization, remeshing, one space variable |
D03PSF | General system of convection-diffusion PDEs, coupled DAEs, method of lines, upwind scheme, remeshing, one space variable |
D05AAF | Linear non-singular Fredholm integral equation, second kind, split kernel |
D05ABF | Linear non-singular Fredholm integral equation, second kind, smooth kernel |
D06CBF | Generates a sparsity pattern of a Finite Element matrix associated with a given mesh |
D06CCF | Renumbers a given mesh using Gibbs method |
E02RAF | Padé approximants |
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) |
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) |
E04NCF | Convex QP problem or linearly-constrained linear least squares problem (dense) |
E04UCF | Minimum, function of several variables, sequential QP method, nonlinear constraints, using function values and optionally first derivatives (comprehensive) |
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) |
E04USF | Minimum of a sum of squares, nonlinear constraints, sequential QP method, using function values and optionally first derivatives (comprehensive) |
E04YCF | Covariance matrix for nonlinear least squares problem (unconstrained) |
F01ABF | Inverse of real symmetric positive definite matrix using iterative refinement |
F02FJF | Selected eigenvalues and eigenvectors of sparse symmetric eigenproblem (Black Box) |
F02WDF | QR factorization, possibly followed by SVD |
F02WGF | Computes leading terms in the singular value decomposition of a real general matrix; also computes corresponding left and right singular vectors |
F02WUF | SVD of real upper triangular matrix (Black Box) |
F02XUF | SVD of complex upper triangular matrix (Black Box) |
F04ABF | Solution of real symmetric positive definite simultaneous linear equations with multiple right-hand sides using iterative refinement (Black Box) |
F04AEF | Solution of real simultaneous linear equations with multiple right-hand sides using iterative refinement (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) |
F04JGF | Least squares (if rank = n) or minimal least squares (if rank < n) solution of m real equations in n unknowns, m ≥ n |
F11DCF | Solution of real sparse nonsymmetric linear system, RGMRES, CGS, Bi-CGSTAB or TFQMR method, preconditioner computed by F11DAF |
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 |
F11DQF | Solution of complex sparse non-Hermitian linear system, RGMRES, CGS, Bi-CGSTAB or TFQMR method, preconditioner computed by F11DNF (Black Box) |
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 |
F11JCF | Solution of real sparse symmetric linear system, conjugate gradient/Lanczos method, preconditioner computed by F11JAF (Black Box) |
F11JEF | Solution of real sparse symmetric linear system, conjugate gradient/Lanczos method, Jacobi or SSOR preconditioner (Black Box) |
F11JQF | Solution of complex sparse Hermitian linear system, conjugate gradient/Lanczos method, preconditioner computed by F11JNF (Black Box) |
F11JSF | Solution of complex sparse Hermitian linear system, conjugate gradient/Lanczos method, Jacobi or SSOR preconditioner (Black Box) |
F11MDF | Real sparse nonsymmetric linear systems, setup for F11MEF |
F12FGF | Selected eigenvalues and, optionally, eigenvectors of a real symmetric banded eigenproblem, driver |
G01AGF | Lineprinter scatterplot of two variables |
G01AHF | Lineprinter scatterplot of one variable against Normal scores |
G01ANF | Calculates approximate quantiles from a data stream of known size |
G01APF | Calculates approximate quantiles from a data stream of unknown size |
G01ARF | Constructs a stem and leaf plot |
G01EMF | Computes probability for the Studentized range statistic |
G01HBF | Computes probabilities for the multivariate Normal distribution |
G01JDF | Computes lower tail probability for a linear combination of (central) χ^{2} variables |
G02ABF | Computes the nearest correlation matrix to a real square matrix, augmented G02AAF to incorporate weights and bounds |
G02AEF | Computes the nearest correlation matrix with k-factor structure to a real square matrix |
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 |
G02DDF | Estimates of linear parameters and general linear regression model from updated model |
G02DEF | Add a new independent variable to a general linear regression model |
G02DGF | Fits a general linear regression model to new dependent variable |
G02DKF | Estimates and standard errors of parameters of a general linear regression model for given constraints |
G02EEF | Fits a linear regression model by forward selection |
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 |
G02HAF | Robust regression, standard M-estimates |
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 |
G02JAF | Linear mixed effects regression using Restricted Maximum Likelihood (REML) |
G02JBF | Linear mixed effects regression using Maximum Likelihood (ML) |
G02KAF | Ridge regression, optimizing a ridge regression parameter |
G02KBF | Ridge regression using a number of supplied ridge regression parameters |
G03ACF | Performs canonical variate analysis |
G03ADF | Performs canonical correlation analysis |
G04EAF | Computes orthogonal polynomials or dummy variables for factor/classification variable |
G05PDF | Generates a realization of a time series from a GARCH process with asymmetry of the form (ε_{t − 1} + γ)^{2} |
G05PEF | Generates a realization of a time series from a GARCH process with asymmetry of the form (|ε_{t − 1}| + γε_{t − 1})^{2} |
G05PFF | Generates a realization of a time series from an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process |
G05PGF | Generates a realization of a time series from an exponential GARCH (EGARCH) process |
G05PJF | Generates a realization of a multivariate time series from a VARMA model |
G05PYF | Generates a random correlation matrix |
G05RZF | Generates a matrix of pseudorandom numbers from a multivariate Normal distribution |
G07BEF | Computes maximum likelihood estimates for parameters of the Weibull distribution |
G07BFF | Estimates parameter values of the generalized Pareto distribution |
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 |
G08AGF | Performs the Wilcoxon one-sample (matched pairs) signed rank test |
G08AKF | Computes the exact probabilities for the Mann–Whitney U statistic, ties in pooled sample |
G08CBF | Performs the one-sample Kolmogorov–Smirnov test for standard distributions |
G08CCF | Performs the one-sample Kolmogorov–Smirnov test for a user-supplied distribution |
G08CDF | Performs the two-sample Kolmogorov–Smirnov test |
G08RAF | Regression using ranks, uncensored data |
G08RBF | Regression using ranks, right-censored data |
G11BBF | Computes multiway table from set of classification factors using given percentile/quantile |
G11BCF | Computes marginal tables for multiway table computed by G11BAF or G11BBF |
G11SAF | Contingency table, latent variable model for binary data |
G12ABF | Computes rank statistics for comparing survival curves |
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) |
G13AJF | Univariate time series, state set and forecasts, from fully specified seasonal ARIMA model |
G13BCF | Multivariate time series, cross-correlations |
G13BEF | Multivariate time series, estimation of multi-input model |
G13BJF | Multivariate time series, state set and forecasts from fully specified multi-input model |
G13DBF | Multivariate time series, multiple squared partial autocorrelations |
G13DDF | Multivariate time series, estimation of VARMA model |
G13DNF | Multivariate time series, sample partial lag correlation matrices, χ^{2} statistics and significance levels |
G13FAF | Univariate time series, parameter estimation for either a symmetric GARCH process or a GARCH process with asymmetry of the form (ε_{t − 1} + γ)^{2} |
G13FCF | Univariate time series, parameter estimation for a GARCH process with asymmetry of the form (|ε_{t − 1}| + γε_{t − 1})^{2} |
G13FEF | Univariate time series, parameter estimation for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process |
G13FGF | Univariate time series, parameter estimation for an exponential GARCH (EGARCH) process |