Multivariate generalized Poisson geometric process model with scale mixtures of normal distributions

Characterizations of Multivariate Normal-Poisson Model

‎Multivariate normal-Poisson model has been recently introduced as a special case of normal stable Tweedie models‎. ‎The model is composed of a univariate Poisson variable‎, ‎and the remaining variables given the Poisson one are independent Gaussian variables with variance the value of the Poisson component‎. ‎Two characterizations of this model are shown‎, ‎...

Characteristic functions of scale mixtures of multivariate skew-normal distributions

Shape mixtures of multivariate skew-normal distributions

Classes of shape mixtures of independent and dependent multivariate skew-normal distributions are considered and some of their main properties are studied. If interpreted from a Bayesian point of view, the results obtained in this paper bring tractability to the problem of inference for the shape parameter, that is, the posterior distribution can be written in analytic form. Robust inference fo...

Multivariate extremes of generalized skew-normal distributions

We explore extremal properties of a family of skewed distributions extended from the multivariate normal distribution by introducing a skewing function π . We give sufficient conditions on the skewing function for the pairwise asymptotic independence to hold. We apply our results to a special case of the bivariate skew-normal distribution and finally support our conclusions by a simulation stud...

On scale mixtures of normal distributions

Suppose that Y has a standard normal distribution and that ohas some distribution on (0, oo) with a continuous or discrete density h(o-) (o-> 0). Then the distribution of X = Yois referred to as a scale mixture of normals, and with a scale mixing density h(o-). A wide class of continuous, unimodal and symmetric distributions on the real line may be constructed as scale mixtures of normals. Many...