This book presents recent developments in multivariate and robust
statistical methods. Featuring contributions by leading experts in
the field it covers various topics, including multivariate and
high-dimensional methods, time series, graphical models, robust
estimation, supervised learning and normal extremes. It will appeal
to statistics and data science researchers, PhD students and
practitioners who are interested in modern multivariate and robust
statistics. The book is dedicated to David E. Tyler on the occasion
of his pending retirement and also includes a review contribution
on the popular Tyler’s shape matrix.
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