- F01 Introduction
- f01ab – Inverse of real symmetric positive-definite matrix using iterative refinement
- f01ad – Inverse of real symmetric positive-definite matrix
- f01bl – Pseudo-inverse and rank of real m by n matrix (m >= n)
- f01br – LU factorization of real sparse matrix
- f01bs – LU factorization of real sparse matrix with known sparsity pattern
- f01bu – ULDL^TU^T factorization of real symmetric positive-definite band matrix
- f01bv – Reduction to standard form, generalized real symmetric-definite banded eigenproblem
- f01ck – Matrix multiplication
- f01cr – Matrix transposition
- f01ct – Sum or difference of two real matrices, optional scaling and transposition
- f01cw – Sum or difference of two complex matrices, optional scaling and transposition
- f01le – LU factorization of real tridiagonal matrix
- f01lh – LU factorization of real almost block diagonal matrix
- f01mc – LDL^T factorization of real symmetric positive-definite variable-bandwidth matrix
- f01qg – RQ factorization of real m by n upper trapezoidal matrix (m <= n)
- f01qj – RQ factorization of real m by n matrix (m <= n)
- f01qk – Operations with orthogonal matrices, form rows of Q, after RQ factorization by f01qj
- f01rg – RQ factorization of complex m by n upper trapezoidal matrix (m <= n)
- f01rj – RQ factorization of complex m by n matrix (m <= n)
- f01rk – Operations with unitary matrices, form rows of Q, after RQ factorization by f01rj
- f01za – Convert real matrix between packed triangular and square storage schemes
- f01zb – Convert complex matrix between packed triangular and square storage schemes
- f01zc – Convert real matrix between packed banded and rectangular storage schemes
- f01zd – Convert complex matrix between packed banded and rectangular storage schemes