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Discussion of “Multivariate Functional Outlier Detection”, by Mia Hubert, Peter Rousseeuw and Pieter Segaert

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  • Davy Paindaveine
  • Germain Van Bever

Abstract

We present a discussion of Hubert et al. ( 2015 )—hereafter, HRS15—that splits into two parts. In the first one, we argue that some structural properties of depth may, in some cases, limit its relevance for outlier detection. We also propose an alternative to bagdistances, which, while still based on depth, does not suffer from the same limitations. In the second part of the discussion, we investigate the possible uses of the weight functions that may enter the various integral functionals considered in HRS15. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Davy Paindaveine & Germain Van Bever, 2015. "Discussion of “Multivariate Functional Outlier Detection”, by Mia Hubert, Peter Rousseeuw and Pieter Segaert," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 223-231, July.
    • Handle: RePEc:spr:stmapp:v:24:y:2015:i:2:p:223-231
    DOI: 10.1007/s10260-015-0307-x
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    References listed on IDEAS

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    1. Davy Paindaveine & Germain Van bever, 2013. "From Depth to Local Depth: A Focus on Centrality," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(503), pages 1105-1119, September.
    2. Mia Hubert & Peter Rousseeuw & Pieter Segaert, 2015. "Multivariate functional outlier detection," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 177-202, July.
    3. Robert Serfling, 2010. "Equivariance and invariance properties of multivariate quantile and related functions, and the role of standardisation," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(7), pages 915-936.
    4. Mia Hubert & Peter Rousseeuw & Pieter Segaert, 2015. "Rejoinder to ‘multivariate functional outlier detection’," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 269-277, July.
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    Cited by:

    1. Francesca Ieva & Anna Maria Paganoni, 2020. "Component-wise outlier detection methods for robustifying multivariate functional samples," Statistical Papers, Springer, vol. 61(2), pages 595-614, April.

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