Comparison of some methods for solving sparse linear least-squares problems
Journal Article
·
· SIAM J. Sci. Stat. Comput.; (United States)
The method of normal equations, the Peters-Wilkinson algorithm and an algorithm based on Givens rotations for solving large sparse linear least squares problems are discussed and compared. Numerical experiments show that the method of normal equations should be considered when the observation matrix is sparse and well conditioned. For ill-conditioned problems, the algorithm based on Givens rotations is preferable.
- Research Organization:
- Univ. of Waterloo, Ontario
- DOE Contract Number:
- W-7405-ENG-26
- OSTI ID:
- 6144201
- Journal Information:
- SIAM J. Sci. Stat. Comput.; (United States), Journal Name: SIAM J. Sci. Stat. Comput.; (United States) Vol. 4:2; ISSN SIJCD
- Country of Publication:
- United States
- Language:
- English
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