Cronbach's alpha is a popular method to measure reliability, eg in quantifying the reliability
of a score to summarize the information of several items in questionnaires. The alpha …

A well-known shortcoming of the traditional canonical correlation analysis (CCA) is the lack
of robustness against outliers. This shortcoming hinders the application of CCA in the case …

The autocorrelation function (acf) and the partial autocorrelation function (pacf) are
elementary tools of linear time series analysis. The sensitivity of the conventional sample acf …

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 …

Very general concepts of scatter, extending the traditional notion of covariance matrices,
have become classical tools in robust multivariate analysis. In many problems of practical …

Abstract Methenitis, SK, Zaras, ND, Spengos, KM, Stasinaki, A-NE, Karampatsos, GP,
Georgiadis, GV, and Terzis, GD. Role of muscle morphology in jumping, sprinting, and …

In a seminal paper, Tyler suggests an M-estimator for shape, which is now known as Tyler's
shape matrix. Tyler's shape matrix is increasingly popular due to its nice statistical …

Background Canonical correlation analysis (CCA) is a multivariate statistical method which
describes the associations between two sets of variables. The objective is to find linear …

We define the minimum covariance determinant functionals for multivariate location and
scatter through trimming functions and establish their existence at any multivariate …

We propose halfspace depth concepts for scatter, concentration and shape matrices. For
scatter matrices, our concept is similar to those from Chen, Gao and Ren [Robust covariance …