The minimum covariance determinant (MCD) method is a highly robust estimator of
multivariate location and scatter, for which a fast algorithm is available. Since estimating the …

The minimum covariance determinant (MCD) estimator is a highly robust estimator of
multivariate location and scatter. It can be computed efficiently with the FAST‐MCD …

This paper proposes a distributionally robust approach to logistic regression. We use the
Wasserstein distance to construct a ball in the space of probability distributions centered at …

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 …

We introduce a new method for robust principal component analysis (PCA). Classical PCA is
based on the empirical covariance matrix of the data and hence is highly sensitive to …

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 …

Supplementary Material for “On the Use of Cauchy Prior Distributions for Bayesian Logistic
Regression”. In the supplementary material, we present additional simulation results for …

A fast and stable algorithm to compute a highly robust estimator for the logistic regression
model is proposed. A criterium for the existence of this estimator at finite samples is derived …

Litter characteristics at birth were recorded in 4 genetic types of sows with differing maternal
abilities. Eighty-two litters from F1 Duroc× Large White sows, 651 litters from Large White …

We recently documented plasma lipid dysregulation in preclinical late-onset Alzheimer's
disease (LOAD). A 10 plasma lipid panel, predicted phenoconversion and provided 90 …