Skip to main content
Log in

Iterative refinement of linear least squares solutions I

  • Published:
BIT Numerical Mathematics Aims and scope Submit manuscript

Abstract

An iterative procedure is developed for reducing the rounding errors in the computed least squares solution to an overdetermined system of equationsAx =b, whereA is anm ×n matrix (mn) of rankn. The method relies on computing accurate residuals to a certain augmented system of linear equations, by using double precision accumulation of inner products. To determine the corrections, two methods are given, based on a matrix decomposition ofA obtained either by orthogonal Householder transformations or by a modified Gram-Schmidt orthogonalization. It is shown that the rate of convergence in the iteration is independent of the right hand side,b, and depends linearly on the condition number, ℳ2135;(A), of the rectangular matrixA. The limiting accuracy achieved will be approximately the same as that obtained by a double precision factorization.

In a second part of this paper the case whenx is subject to linear constraints and/orA has rank less thann is covered. Here also ALGOL-programs embodying the derived algorithms will be given.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Bauer, F. L.,Elimination with Weighted Row Combinations for Solving Linear Equations and Least Squares Problems, Num. Math. 7 (1965), 338–352.

    Google Scholar 

  2. Björck, Å.,Solving Linear Least Squares Problems by Gram-Schmidt Orthogonalization, BIT 7 (1967), 1–21.

    Google Scholar 

  3. Collatz, L.,Funktionalanalysis und Numerische Mathematik, Berlin: Springer-Verlag (1964).

    Google Scholar 

  4. Golub, G. H.,Numerical Methods for Solving Linear Least Squares Problems, Num. Math. 7 (1965), 206–216.

    Google Scholar 

  5. Golub, G. H. and Wilkinson, J. H.,Note on the Iterative Refinement of Least Squares Solution, Num. Math. 9 (1966), 139–148.

    Google Scholar 

  6. Martin, R. S., Peters, G. and Wilkinson, J. H.,Iterative Refinement of the Solution of a Positive Definite System of Equations, Num. Math. 8, (1966), 203–216.

    Google Scholar 

  7. Moler, C. B.,Iterative Refinement in Floating Point, J. Assoc. Comput. Mach. 14, (1967), 316–321.

    Google Scholar 

  8. Wilkinson, J. H.,Rounding Errors in Algebraic Processes, London: Her Majesty's Stationary Office; Englewood Cliffs, N.J.: Prentice-Hall 1963.

    Google Scholar 

  9. Wilkinson, J. H.,Error Analysis of Transformations Based on the Use of Matrices of the Form I-2ww T, Error in Digital Computations. Volume II. Rall, L. B. ed. New York: John Wiley (1965), 77–101.

    Google Scholar 

Download references

Authors

Additional information

This work was sponsored by the Swedish Natural Science Research Council.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Björck, Å. Iterative refinement of linear least squares solutions I. BIT 7, 257–278 (1967). https://doi.org/10.1007/BF01939321

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01939321

Keywords

Navigation