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 …

Like its bestselling predecessor, Multilevel Modeling Using R, Second Edition provides the
reader with a helpful guide to conducting multilevel data modeling using the R software …

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 …

This book reviews the state-of-the-art advances in skew-elliptical distributions and provides
many new developments in a single volume, collecting theoretical results and applications …

Linear mixed models with normally distributed response are routinely used in longitudinal
data. However, the accuracy of the assumed normal distribution is crucial for valid inference …

Parametric families of multivariate nonnormal distributions have received considerable
attention in the past few decades. The authors propose a new definition of a selection …

In this paper we consider a flexible class of models, with elements that are finite mixtures of
multivariate skew-normal independent distributions. A general EM-type algorithm is …

Gaussian scale mixtures are constructed as Gaussian processes with a random variance.
They have non-Gaussian marginals and can exhibit asymptotic dependence unlike …

A flexible class of probability distributions, convenient for modeling data with skewness
behavior, discrepant observations and population heterogeneity is presented. The elements …

This paper proposes a new heavy-tailed and alternative slash type distribution on a
bounded interval via a relation of a slash random variable with respect to the standard …