Solution of augmented linear systems using orthogonal factorizations
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Publication:1343038
DOI10.1007/BF01935013zbMath0822.65021WikidataQ114233891 ScholiaQ114233891MaRDI QIDQ1343038
Christopher C. Paige, Åke Björck
Publication date: 15 October 1995
Published in: BIT (Search for Journal in Brave)
numerical stabilityleast squaresaugmented systemHouseholder transformationsGram-Schmidt algorithmiterative refinements\(QR\)-factorizationsseminormal equations
Numerical solutions to overdetermined systems, pseudoinverses (65F20) Roundoff error (65G50) Direct numerical methods for linear systems and matrix inversion (65F05) Orthogonalization in numerical linear algebra (65F25)
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Cites Work
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- Error analysis of algorithms for computing the projection of a point onto a linear manifold
- The weak and strong stability of algorithms in numerical linear algebra
- On the augmented system approach to sparse least-squares problems
- Stability analysis of the method of seminormal equations for linear least squares problems
- Note on the iterative refinement of least squares solution
- Loss and Recapture of Orthogonality in the Modified Gram–Schmidt Algorithm
- The Strong Stability of Algorithms for Solving Symmetric Linear Systems
- The Accuracy of Solutions to Triangular Systems
- An Error Analysis of a Method for Solving Matrix Equations
- Iterative refinement of linear least squares solutions I
- Solving linear least squares problems by Gram-Schmidt orthogonalization