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Selected Algorithms for Robust M- and L-Regression Estimators

In: Developments in Robust Statistics

Author

Listed:
  • J. Antoch

    (Charles University, Department of Probability and Statistics)

  • H. Ekblom

    (Luleå University of Technology, Department of Mathematics)

Abstract

Summary The main objective of this survey paper is to discuss the numerical aspects of robust estimation in the linear model. Due to the space available we concentrate on M - and L - estimators, both nonrecursive and recursive ones. The emphasis is on numerical algorithms and computational efficiency, not on their statistical properties. While the main interest is on convex ϱ-functions generating M- estimators, it is pointed out that for non-convex ϱ-functions one can run into serious trouble and that the recursion can give little help in finding the optimal solution.

Suggested Citation

  • J. Antoch & H. Ekblom, 2003. "Selected Algorithms for Robust M- and L-Regression Estimators," Springer Books, in: Rudolf Dutter & Peter Filzmoser & Ursula Gather & Peter J. Rousseeuw (ed.), Developments in Robust Statistics, pages 32-49, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-57338-5_3
    DOI: 10.1007/978-3-642-57338-5_3
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