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arXiv · 1406.6031

Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination

Claudio Agostinelli·Andy Leung·Victor J. Yohai·Ruben H. Zamar
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Abstract

Multivariate location and scatter matrix estimation is a cornerstone in multivariate data analysis. We consider this problem when the data may contain independent cellwise and casewise outliers. Flat data sets with a large number of variables and a relatively small number of cases are common place in modern statistical applications. In these cases global down-weighting of an entire case, as performed by traditional robust procedures, may lead to poor results. We highlight the need for a new generation of robust estimators that can efficiently deal with cellwise outliers and at the same time show good performance under casewise outliers.

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Claudio Agostinelli, Andy Leung, Victor J. Yohai, Ruben H. Zamar. 2014-06-23. Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination. https://arxiv.org/abs/1406.6031

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