Robust estimation of multivariate location and scatter in the presence   of cellwise and casewise contamination
  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. 
Claudio Agostinelli, Andy Leung, Victor J. Yohai and Ruben H. Zamar
math.ST stat.TH