Selected Algorithms for Robust M- and L-Regression Estimators

J. Antoch () and H. Ekblom ()
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J. Antoch: Charles University, Department of Probability and Statistics
H. Ekblom: Luleå University of Technology, Department of Mathematics

A chapter in Developments in Robust Statistics, 2003, pp 32-49 from Springer

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.

Keywords: Least squares estimator; M- and L- estimators; Recursive M-estimators; IRLS; Newton’s method; Simplex method; Dual simplex algorithm (search for similar items in EconPapers)
Date: 2003
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-57338-5_3

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DOI: 10.1007/978-3-642-57338-5_3

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