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The finite sample breakdown point of PCS

Author

Listed:
  • Schmitt, Eric
  • Öllerer, Viktoria
  • Vakili, Kaveh

Abstract

The Projection Congruent Subset (PCS) is a new method for finding multivariate outliers. PCS returns an outlyingness index which can be used to construct affine equivariant estimates of multivariate location and scatter. In this note, we derive the finite sample breakdown point of these estimators.

Suggested Citation

  • Schmitt, Eric & Öllerer, Viktoria & Vakili, Kaveh, 2014. "The finite sample breakdown point of PCS," Statistics & Probability Letters, Elsevier, vol. 94(C), pages 214-220.
    • Handle: RePEc:eee:stapro:v:94:y:2014:i:c:p:214-220
    DOI: 10.1016/j.spl.2014.07.026
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    References listed on IDEAS

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    1. Vakili, Kaveh & Schmitt, Eric, 2014. "Finding multivariate outliers with FastPCS," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 54-66.
    2. Adrover, Jorge G. & Yohai, Víctor J., 2010. "A new projection estimate for multivariate location with minimax bias," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1400-1411, July.
    3. Maronna, Ricardo A. & Stahel, Werner A. & Yohai, Victor J., 1992. "Bias-robust estimators of multivariate scatter based on projections," Journal of Multivariate Analysis, Elsevier, vol. 42(1), pages 141-161, July.
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