A Simple Test to Identify Good Solutions of Redescending M Estimating Equations for Regression

O. Arslan ()
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O. Arslan: University of Cukurova, Department of Mathematics

A chapter in Developments in Robust Statistics, 2003, pp 50-61 from Springer

Abstract: Summary Since recent interests are to consider not just one solution but all possible solutions to the redescending M estimating equations to identify possible multiple structure in a data set (Morgenthaler, 1990; Meer and Tyler, 1998), the focus in this paper is the re-descending M estimators for regression. We use multiple local minima for finding particular structures, such as lines, in the data set by associating them with the local minima in a re-descending M estimation problem for regression. A simple qualitative measure is constructed to assess the importance of each local minimum point, and hence importance of each fit to the data. This testing procedure allows us to distinguish between good and bad fits to the data.

Keywords: Robust regression; Redescending M-estimator; Robustness; Hessian matrix; Local minimum point (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_4

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DOI: 10.1007/978-3-642-57338-5_4

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