On the efficient computation of robust regression estimators

Authors:
Salvador Flores
Affiliations:
Université de Toulouse, UPS, Institut de Mathématiques, UMR CNRS 5219, 118 route de Narbonne, F-31062 Toulouse Cedex 9, France
Venue:
Computational Statistics & Data Analysis
Year:
2010

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Abstract

The problem of providing efficient and reliable robust regression algorithms is considered. The impact of global optimization methods, such as stopping conditions and clustering techniques, in the calculation of robust regression estimators is investigated. The use of stopping conditions permits us to devise new algorithms that perform as well as the existing algorithms in less time and with adaptive algorithm parameters. Clustering global optimization is shown to be a general framework encompassing many of the existing algorithms.