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Statistical Methods & Applications

, Volume 27, Issue 4, pp 603–604 | Cite as

Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample” by Andrea Cerioli, Marco Riani, Anthony C. Atkinson and Aldo Corbellini

  • Ricardo A. Maronna
  • Víctor J. Yohai
Comment

Abstract

Comments on the “monitoring” method and its relationships with other robust estimation methods.

Keywords

Forward search Outlier detection MM estimation DCML estimator 

References

  1. Cerioli A, Riani M, Atkinson AC, Corbellini A (2018) The power of monitoring: how to make the most of a contaminated multivariate sample, Stat Methods Appl (in press)Google Scholar
  2. Maronna RA, Yohai VJ (2014) High finite-sample efficiency and robustness based on distance-constrained maximum likelihood. Comput Stat Data Anal 83:262–274MathSciNetCrossRefzbMATHGoogle Scholar
  3. Maronna RA, Yohai VJ (2017) Robust and efficient estimation of high dimensional scatter and location. Comput Stat Data Anal 109:64–75CrossRefzbMATHGoogle Scholar
  4. Smucler E, Yohai VJ (2017) Robust and sparse estimators for linear regression models. Comput Stat Data Anal 111:116–130MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.University of La PlataLa PlataArgentina
  2. 2.University of Buenos Aires and CONICETBuenos AiresArgentina

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