Deviation Maximization for Rank-Revealing QR Factorizations
Numerical Analysis
2022-06-03 v1 Numerical Analysis
Abstract
In this paper we introduce a new column selection strategy, named here ``Deviation Maximization", and apply it to compute rank-revealing QR factorizations as an alternative to the well known block version of the QR factorization with the column pivoting method, called QP3 and currently implemented in LAPACK's xgeqp3 routine. We show that the resulting algorithm, named QRDM, has similar rank-revealing properties of QP3 and better execution times. We present numerical test results on a wide data set of numerically singular matrices, which has become a reference in the recent literature.
Cite
@article{arxiv.2106.03138,
title = {Deviation Maximization for Rank-Revealing QR Factorizations},
author = {Monica Dessole and Fabio Marcuzzi},
journal= {arXiv preprint arXiv:2106.03138},
year = {2022}
}
Comments
31 pages, 7 figures, submitted to Numerical Algorithms