The minimum volume ellipsoid (MVE) estimator is based on the smallest volume ellipsoid
that covers h of the n observations. It is an affine equivariant, high‐breakdown robust …

A new edition of this popular text on robust statistics, thoroughly updated to include new and
improved methods and focus on implementation of methodology using the increasingly …

This revised book provides a thorough explanation of the foundation of robust methods,
incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and …

When applying a statistical method in practice it often occurs that some observations deviate
from the usual assumptions. However, many classical methods are sensitive to outliers. The …

A class of projection-based depth functions is introduced and studied. These projection-
based depth functions possess desirable properties of statistical depth functions and their …

A new multivariate concept of quantile, based on a directional version of Koenker and
Bassett's traditional regression quantiles, is introduced for multivariate location and multiple …

Despite the absence of a natural ordering of Euclidean space for dimensions greater than
one, the effort to define vector‐valued quantile functions for multivariate distributions has …

Motivation: Principal components analysis (PCA) is a very popular dimension reduction
technique that is widely used as a first step in the analysis of high-dimensional microarray …

This book gives a non-technical overview of robust data reduction techniques, encouraging
the use of these important and useful methods in practical applications. The main areas …

We introduce a robust method for multivariate regression based on robust estimation of the
joint location and scatter matrix of the explanatory and response variables. As a robust …