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Comments on “The power of monitoring: how to make the most of a contaminated multivariate sample”


  • L. A. García-Escudero

    () (Universidad de Valladolid)

  • A. Gordaliza

    (Universidad de Valladolid)

  • C. Matrán

    (Universidad de Valladolid)

  • A. Mayo-Iscar

    (Universidad de Valladolid)


Abstract These are comments on the invited paper “The power of monitoring: How to make the most of a contaminated multivariate sample” by Andrea Cerioli, Marco Riani, Anthony Atkinson and Aldo Corbellini.

Suggested Citation

  • L. A. García-Escudero & A. Gordaliza & C. Matrán & A. Mayo-Iscar, 2018. "Comments on “The power of monitoring: how to make the most of a contaminated multivariate sample”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(4), pages 605-608, December.
  • Handle: RePEc:spr:stmapp:v:27:y:2018:i:4:d:10.1007_s10260-017-0415-x
    DOI: 10.1007/s10260-017-0415-x

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    References listed on IDEAS

    1. J. A. Cuesta‐Albertos & C. Matrán & A. Mayo‐Iscar, 2008. "Robust estimation in the normal mixture model based on robust clustering," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 779-802, September.
    2. Neykov, N. & Filzmoser, P. & Dimova, R. & Neytchev, P., 2007. "Robust fitting of mixtures using the trimmed likelihood estimator," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 299-308, September.
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    Clustering; Robustness; Monitoring;


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