Efficient Solution Of The Rank-Deficient Linear Least Squares Problem

In this paper we present several new fast and reliable algorithms for solving rank-deficient linear least squares problems by means of the complete orthogonal decomposition. Experimental comparison of our algorithms with the existing implementations in LAPACK on a wide range of platforms shows considerable performance improvements. Moreover, for full-rank matrices the performance of the new algorithm is very close to that of the fast method based on QR factorization, thus providing a valuable general tool for full-rank matrices, rank-deficient matrices, and those matrices with unknown rank.