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Testing Numerical Methods Solving the Linear Least Squares Problem

In: Statistical Inference, Econometric Analysis and Matrix Algebra

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  • Claus Weihs

    (Technische Universität Dortmund, Fakultät Statistik)

Abstract

The paper derives a general method for testing algorithms solving the Least-Squares-Problem (LS-Problem) of a linear equation system. This test method includes the generation of singular test matrices with arbitrary condition, full column rank and exactly representable generalized inverses, as well as a method for choosing general right hand sides. The method is applied to three LS-Problem solvers in order to assess under what conditions the error in the least squares solution is only linearly dependent on the condition number.

Suggested Citation

  • Claus Weihs, 2009. "Testing Numerical Methods Solving the Linear Least Squares Problem," Springer Books, in: Bernhard Schipp & Walter Kräer (ed.), Statistical Inference, Econometric Analysis and Matrix Algebra, pages 333-347, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-2121-5_23
    DOI: 10.1007/978-3-7908-2121-5_23
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