On the efficient computation of robust regression estimators

Salvador Flores

Computational Statistics & Data Analysis, 2010, vol. 54, issue 12, 3044-3056

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.

Keywords: Robust; regression; Clustering; Global; optimization; Stopping; conditions (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (1)

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