In this paper we introduce the class of Lp scale mixture random vectors which includes beta-independent random vectors and Lp Dirichlet ones. We derive several conditional limit results assuming that the associated random radius of the Lp scale mixture random vectors have distribution function in the max-domain of attraction of a univariate extreme value distribution function. As an application...

We propose a robust Poisson geometric process model with heavy-tailed distributions to cope with the problem of outliers as it may lead to an overestimation of mean and variance resulting in inaccurate interpretations of the situations. Two heavy-tailed distributions namely Student’s t and exponential power distributions with different tailednesses and kurtoses are used and they are represented...

In recent years, the mixture of two-component normal distributions (MixN) has attracted considerable interest due to its flexibility in capturing a variety density shapes. this paper, we investigate problem discretizing MixN by fixed number points under minimum mean squared error (MSE-RPs). Motivated Fang-He algorithm, provide an effective computational procedure with high precision for generat...

A limiting feature of previous work on growth mixture modeling is the assumption of normally distributed variables within each latent class. With strongly non-normal outcomes, this means that several latent classes are required to capture the observed variable distributions. Being able to relax the assumption of within-class normality has the advantage that a non-normal observed distribution do...

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...