NAG Fortran Library

Chapter 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    ULD LT UT 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

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© The Numerical Algorithms Group Ltd, Oxford UK. 2001