Mixtures of multivariate power exponential distributions.

Identifiability of finite mixtures of elliptical distributions

We present general results on the identifiability of finite mixtures of elliptical distributions under conditions on the characteristic generators or density generators. Examples include the multivariate t distribution, symmetric stable laws, exponential power and Kotz distributions. In each case, the shape parameter is allowed to vary in the mixture, in addition to the location vector and the ...

On Bivariate Generalized Exponential-Power Series Class of Distributions

In this paper, we introduce a new class of bivariate distributions by compounding the bivariate generalized exponential and power-series distributions. This new class contains the bivariate generalized exponential-Poisson, bivariate generalized exponential-logarithmic, bivariate generalized exponential-binomial and bivariate generalized exponential-negative binomial distributions as specia...

Some New Characterization Results on Exponential and Related Distributions

Models for dependent extremes using stable mixtures Running/short title: Models for dependent extremes

Abstract: This paper unifies and extends results on a class of multivariate Extreme Value (EV) models studied by Hougaard, Crowder, and Tawn. In these models both unconditional and conditional distributions are EV, and all lower-dimensional marginals and maxima belong to the class. This leads to substantial economies of understanding, analysis and prediction. One interpretation of the models is...

A Probabilistic Expectation Maximization Algorithm for Multivariate Laplacian Mixtures

Estimating parameters of mixture models is a typical application of the expectation maximization (EM) algorithm. For the family of multivariate exponential power (MEP) distributions, which is a generalization of the well known multivariate Gaussian distribution, we introduce an approximative EM algorithm, and a probabilistic variant called stochastic EM algorithm, which provides a significant s...