Solving least squares problems - Lawson, Charles L. 194X- (Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104), 1995)
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Includes bibliographical references (s. 312-326) and index
Preface to the Classics edition -- Preface -- Chapter 1. Introduction -- Chapter 2. Analysis of the least squares problem -- Chapter 3. Orthogonal decomposition by certain elementary orthogonal transformations -- Chapter 4. Orthogonal decomposition by singular value decomposition -- Chapter 5. Perturbation theorems for singular values -- Chapter 6. Bounds for the condition number of a triangular matrix -- Chapter 7. The pseudoinverse -- Chapter 8. Perturbation bounds for the pseudoinverse -- Chapter 9. Perturbation bounds for the solution of problem LS -- Chapter 10. Numerical computations using elementary orthogonal transformations -- Chapter 11. Computing the solution for the overdetermined or exactly-- determined full rank problem -- Chapter 12. Computation of the covariance matrix of the solution parameters -- Chapter 13. Computing the solution for the underdetermined full rank problem -- Chapter 14. Computing the solution for problem LS with possibly deficient pseudorank -- Chapter 15. Analysis of computing errors for householder transformations -- Chapter 16. Analysis of computing errors for the problem LS -- Chapter 17. Analysis of computing errors for the problem LS using mixed precision arithmetic -- Chapter 18. Computation of the singular value decomposition and the solution of problem LS -- Chapter 19. Other methods for least squares problems --
Chapter 20. Linear least squares with linear equality constraints using a basis of the null space -- Chapter 21. Linear least squares with linear equality constraints by direct elimination -- Chapter 22. Linear least squares with linear equality constraints by weighting -- Chapter 23. Linear least squares with linear inequality constraints -- Chapter 24. Modifying a QR decomposition to add or remove column vectors -- Chapter 25. Practical analysis of least squares problems -- Chapter 26. Examples of some methods of analyzing a least squares problem -- Chapter 27. Modifying a QR decomposition to add or remove row vectors with Application to sequential processing of problems having a large or banded coefficient matrix -- Appendix A. Basic linear algebra including projections -- Appendix B. Proof of global quadratic convergence of the QR algorithm -- Appendix C. Description and use of FORTRAN codes for solving problem LS -- Appendix D. Developments from 1974 to 1995 -- Bibliography -- Index