Algorithm 782: Codes for rank-revealing QR factorizations of dense matrices

摘要

This article describes a suite of codes as well as associated testing and timing drivers for computing rank-revealing QR (RRQR) factorizations of dense matrices. The main contribution is an efficient block algorithm for approximating an RRQR factorization, employing a windowed version of the commonly used Golub pivoting strategy and improved versions of the RRQR algorithms for triangular matrices originally Suggested by Chandrasekaran and Ipsen and by Pan and Tang, respectively. We highlight usage and features of these codes. References: 3