Non-normal mixture distributions have received increasing attention in recent years. Finite mixtures of multivariate skew-symmetric distributions, in particular, the skew normal and skew t-mixture models, are emerging as promising extensions to the traditional normal and t-mixture models. Most of these parametric families of skew distributions are closely related, and can be classified into fou...

In this paper, we derive recurrence relations for cumulative distribution functions (cdf’s) of bivariate t and extended skew-t distributions. These recurrence relations are over ν (the degrees of freedom), and starting from the known results for ν = 1 and ν = 2, they will allow for the recursive evaluation of the distribution function for any other positive integral value of ν. Then, we conside...

Normality of random effects and error terms is a routine assumption for linear effects mixed models. However, such assumption may be unrealistic, obscuring important features of withinand among-unit variation. A simple and robust Bayesian parametric approach that relaxes this assumption by using a multivariate Skew elliptical distributions, which includes the Skew-t, Skew-normal, t-Student, and...

A diversity of spin Hall effects in metallic systems is known to rely on Mott skew scattering. In this work its high-temperature counterpart, phonon skew scattering, which is expected to be of foremost experimental relevance, is investigated. In particular, the phonon skew scattering spin Hall conductivity is found to be practically T independent for temperatures above the Debye temperature T_{...

In this paper, we introduce a mixture of skew-t factor analyzers as well as a family of mixture models based thereon. The mixture of skew-t distributions model that we use arises as a limiting case of the mixture of generalized hyperbolic distributions. Like their Gaussian and t-distribution analogues, our mixture of skew-t factor analyzers are very well-suited to the model-based clustering of ...

In this work we approach the problem of model comparison between skew families. For the univariate skew model, we measure the sensitivity of the skewness parameter using the L1-distance between symmetric and asymmetric models and we obtain explicit expressions for some of these models. The main result is that the L1-distance between a representable elliptical distribution and a representable sk...

This paper describea an algorilhm to estimate ihe tezt skew angle in a document image. The algorithm utilizes the recursive morphological transforms and yield8 accurate estimates of tezl skew angles on a large document image data set. The algorithm computes the optimal pcrrameter settings on the fly without any human interaction. In 2hM automatic mode, ezperimental resulti indicate that the alg...

Multivariate stochastic volatility models with skew distributions are proposed. Exploiting Cholesky stochastic volatility modeling, univariate stochastic volatility processes with leverage effect and generalized hyperbolic skew t-distributions are embedded to multivariate analysis with time-varying correlations. Bayesian prior works allow this approach to provide parsimonious skew structure and...