Fast Robust Variable Selection

Stefan Aelst (), Jafar A. Khan () and Ruben H. Zamar ()
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Stefan Aelst: Ghent University, Department of Applied Mathematics and Computer Science
Jafar A. Khan: University of Dhaka, Department of Statistics
Ruben H. Zamar: University of British Columbia, Department of Statistics

A chapter in COMPSTAT 2008, 2008, pp 359-370 from Springer

Abstract: Abstract We discuss some computationally efficient procedures for robust variable selection in linear regression. A key component in these procedures is the computation of robust correlations between pairs of variables. We show that the robust variable selection procedures can easily handle missing data under the assumption that data are missing completely at random.

Keywords: correlation; missing data; robustness; variable selection (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-2084-3_30

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DOI: 10.1007/978-3-7908-2084-3_30

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