NAG Fortran Library

F01 - Matrix Factorizations


Chapter Introduction
F01ABF Inverse of real symmetric positive-definite matrix using iterative refinement
F01ADF Inverse of real symmetric positive-definite matrix
F01BLF Pseudo-inverse and rank of real m by n matrix (m >= n)
F01BRF LU factorization of real sparse matrix
F01BSF LU factorization of real sparse matrix with known sparsity pattern
F01BUF ULDLTUT factorization of real symmetric positive-definite band matrix
F01BVF Reduction to standard form, generalized real symmetric-definite banded eigenproblem
F01CKF Matrix multiplication
F01CRF Matrix transposition
F01CTF Sum or difference of two real matrices, optional scaling and transposition
F01CWF Sum or difference of two complex matrices, optional scaling and transposition
F01LEF LU factorization of real tridiagonal matrix
F01LHF LU factorization of real almost block diagonal matrix
F01MCF LDLT factorization of real symmetric positive-definite variable-bandwidth matrix
F01QGF RQ factorization of real m by n upper trapezoidal matrix (m <= n)
F01QJF RQ factorization of real m by n matrix (m <= n)
F01QKF Operations with orthogonal matrices, form rows of Q, after RQ factorization by F01QJF
F01RGF RQ factorization of complex m by n upper trapezoidal matrix (m <= n)
F01RJF RQ factorization of complex m by n matrix (m <= n)
F01RKF Operations with unitary matrices, form rows of Q, after RQ factorization by F01RJF
F01ZAF Convert real matrix between packed triangular and square storage schemes
F01ZBF Convert complex matrix between packed triangular and square storage schemes
F01ZCF Convert real matrix between packed banded and rectangular storage schemes
F01ZDF Convert complex matrix between packed banded and rectangular storage schemes


© The Numerical Algorithms Group Ltd, Oxford UK. 1999