Finite mixtures of multivariate skew t (MST) distributions have proven to be useful in
modelling heterogeneous data with asymmetric and heavy tail behaviour. Recently, they …

Skew-normal and skew-t distributions have proved to be useful for capturing skewness and
kurtosis in data directly without transformation. Recently, finite mixtures of such distributions …

We present the R package mixsmsn, which implements routines for maximum likeli-hood
estimation (via an expectation maximization EM-type algorithm) in finite mixture models with …

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 …

This paper presents a robust probabilistic mixture model based on the multivariate skew-t-
normal distribution, a skew extension of the multivariate Student'st distribution with more …

Modeling based on finite mixture distributions is a rapidly develo** area with an exploding
range of applications. Finite mixture models are nowadays applied in such diverse areas as …

This paper deals with the problem of maximum likelihood estimation for a mixture of skew
Student-t-normal distributions, which is a novel model-based tool for clustering …

A class of nonparametric hierarchical mixtures is considered for Bayesian density
estimation. This class, namely mixtures of parametric densities on the positive reals with a …

The goal of constructing models from examples has been approached from different
perspectives. Statistical methods have been widely used and proved effective in generating …

In this article, we propose mixtures of skew Laplace normal (SLN) distributions to model both
skewness and heavy-tailedness in the neous data set as an alternative to mixtures of skew …