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• 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