Outlier detection has been a topic in statistics for centuries. Over mainly the last two
decades, there has been also an increasing interest in the database and data mining …

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 …

Testing for outliers with conformal p-values Page 1 The Annals of Statistics 2023, Vol. 51, No.
1, 149–178 https://doi.org/10.1214/22-AOS2244 © Institute of Mathematical Statistics, 2023 …

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 …

Nonparametric correlation estimators as the Kendall and Spearman correlation are widely
used in the applied sciences. They are often said to be robust, in the sense of being resistant …

Requiring no prior training, Modern Statistics for the Social and Behavioral Sciences
provides a two-semester, graduate-level introduction to basic statistical techniques that …

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 …

Cluster-weighted modeling (CWM) is a mixture approach to modeling the joint probability of
data coming from a heterogeneous population. Under Gaussian assumptions, we …

Outlier detection is an integral component of statistical modelling and estimation. For high-
dimensional data, classical methods based on the Mahalanobis distance are usually not …

The contrast of fraud in international trade is a crucial task of modern economic regulations.
We develop statistical tools for the detection of frauds in customs declarations that rely on …