Robust estimators of covariance matrix and multivariate location under the independent contamination model

CLAUDIO AGOSTINELLI; ANDY LEUNG; VÍCTOR J. YOHAI; RUBEN H. ZAMAR

Rio de Janeiro

Congreso; ISI 2015; 2015

Brazilian lnstitute of Geography and Statistics (IBGE)

Multivariate location and scatter matrix estimation is a cornerstone in multivariatedata 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