A direct method for sparse least squares problems with lower and upper bounds
type: Item
instance of: scholarly article
title: A direct method for sparse least squares problems with lower and upper bounds
zbMATH Open document ID: 0659.65039
DOI: 10.1007/BF01403888
author: Åke Björck
published in: Numerische Mathematik
publication date: 1988-01-01T00:00:00Z
full work available at URL: https://eudml.org/doc/133301
review text: The least squares problem \(\| Ax-b\|_ 2\to Min\). (the solution of which being subject to the additional restriction \(1\leq x\leq u)\) is solved by QR-factorization (using SPARSEPAK), followed by a stable updating procedure for R. The main point is that the updating avoids fill-in and uses the fixed data structure of the factor R. Comparing numerical tests between the new method and the algorithm NNLS of \textit{C. L. Lawson} and \textit{R. J. Hanson} (Solving least squares problems. (1974; M.R. 51.2270)] show remarkable savings both in CPU-time and in storage requirements.
reviewed by: G.Maeß
Mathematics Subject Classification ID: 65F20
Mathematics Subject Classification ID: 65F05
zbMATH DE Number: 4078638
zbMATH Keywords: sparse matrices
zbMATH Keywords: fill-in comparison of methods
zbMATH Keywords: least squares problem
zbMATH Keywords: QR-factorization
zbMATH Keywords: stable updating
zbMATH Keywords: numerical tests
zbMATH Keywords: M.R. 51.2270
describes a project that uses: symrcm
describes a project that uses: LINPACK
describes a project that uses: SPARSPAK
MaRDI profile type: Publication
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OpenAlex ID: W17198020
description: scientific article; zbMATH DE number 4078638