Multivariate location and scatter matrix estimation under cellwise and casewise contamination

@article{Leung2017MultivariateLA,
  title={Multivariate location and scatter matrix estimation under cellwise and casewise contamination},
  author={Andy Leung and Victor J. Yohai and Ruben H. Zamar},
  journal={Comput. Stat. Data Anal.},
  year={2017},
  volume={111},
  pages={59-76}
}
We consider the problem of multivariate location and scatter matrix estimation when the data contain cellwise and casewise outliers. Agostinelli et al. (2015) propose a two-step approach to deal with this problem: first, apply a univariate filter to remove cellwise outliers and second, apply a generalized S-estimator to downweight casewise outliers. We improve this proposal in three main directions. First, we introduce a consistent bivariate filter to be used in combination with the univariate… 
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Comments on: Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination
TLDR
This paper proposes an estimator that is specifically designed to tackle the combination of cellwise (ICM) and casewise (THCM) outliers and makes a point that the methods developed so far can handle one type of outliers or the other, but not yet both.
Comments on: Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination
TLDR
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