This chapter reviews multivariate modeling using copulas with illustrative applications in
engineering such as multivariate process control and degradation analysis. A copula …

Interest in the skew-normal and related families of distributions has grown enormously over
recent years, as theory has advanced, challenges of data have grown, and computational …

Linear structural equation modeling has become an indispensable methodology for
specifying, estimating, and testing hypothesized interrelationships among a set of …

A fairly general procedure is studied to perturb a multivariate density satisfying a weak form
of multivariate symmetry, and to generate a whole set of non-symmetric densities. The …

Complex elliptically symmetric (CES) distributions have been widely used in various
engineering applications for which non-Gaussian models are needed. In this overview …

Almost all the results available in the literature on multivariate t-distributions published in the
last 50 years are now collected together in this comprehensive reference. Because these …

In this paper we introduce a Wasserstein-type distance on the set of Gaussian mixture
models. This distance is defined by restricting the set of possible coupling measures in the …

Within the context of flexible parametric families of distributions, much work has been
dedicated in recent years to the theme of skew-symmetric distributions, or symmetry …

Our object in writing this book is to present the main results of the modern theory of
multivariate statistics to an audience of advanced students who would appreciate a concise …

When the multivariate normality assumption is violated in structural equation modeling, a
leading remedy involves estimation via normal theory maximum likelihood with robust …