In robust estimation one frequently needs an initial or auxiliary estimate of scale. For this one
usually takes the median absolute deviation MAD n= 1.4826 med,{| xi− med jxj|}, because it …

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 …

By starting from a natural class of robust estimators for generalized linear models based on
the notion of quasi-likelihood, we define robust deviances that can be used for stepwise …

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 …

Robust variable selection procedures through penalized regression have been gaining
increased attention in the literature. They can be used to perform variable selection and are …

We investigate the performance of robust estimates of multivariate location under
nonstandard data contamination models such as componentwise outliers (ie, contamination …

Robust statistical methods were developed to supplement the classical procedures when
the data violate classical assumptions. They are ideally suited to applied research across a …

In this article we introduce a new type of positive-breakdown regression method, called a
generalized S-estimator (or GS-estimator), based on the minimization of a generalized M …

Untitled Page 1 Page 2 Information Science and Statistics Series Editors: M. Jordan J.
Kleinberg B. Schölkopf Page 3 Information Science and Statistics For other titles published in …

The concept of breakdown point was introduced by Hampel [Ph. D. dissertation (1968), Univ.
California, Berkeley; Ann. Math. Statist. 42 (1971) 1887–1896] and developed further by …