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Improving bias-robustness of regression estimates through projections

Author

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  • Maronna, Ricardo A.
  • Barrera, Matías Salibian
  • Yohai, Víctor J.

Abstract

We define a robust procedure to "correct" a regression estimate along the directions in predictor space where the fit is worse. When is the least median of squares estimate, the "corrected estimate" has a smaller maximum asymptotic bias under contamination, and a much better finite-sample behavior than

Suggested Citation

  • Maronna, Ricardo A. & Barrera, Matías Salibian & Yohai, Víctor J., 2000. "Improving bias-robustness of regression estimates through projections," Statistics & Probability Letters, Elsevier, vol. 47(2), pages 149-158, April.
    • Handle: RePEc:eee:stapro:v:47:y:2000:i:2:p:149-158
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    References listed on IDEAS

    as
    1. Hawkins, Douglas M., 1993. "The feasible set algorithm for least median of squares regression," Computational Statistics & Data Analysis, Elsevier, vol. 16(1), pages 81-101, June.
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