Journal
TEST
Volume 24, Issue 3, Pages 441-461Publisher
SPRINGER
DOI: 10.1007/s11749-015-0450-6
Keywords
Robust estimation; Multivariate location and scatter; Multivariate data analysis; Cellwise contamination
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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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