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Fast Robust Variable Selection

In: Compstat 2008

Author

Listed:
  • 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)

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.

Suggested Citation

  • Stefan Aelst & Jafar A. Khan & Ruben H. Zamar, 2008. "Fast Robust Variable Selection," Springer Books, in: Paula Brito (ed.), Compstat 2008, pages 359-370, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-2084-3_30
    DOI: 10.1007/978-3-7908-2084-3_30
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