Abstract Mixture of Experts (MoE) is a popular framework for modeling heterogeneity in data for regression, classification and clustering. For continuous data which we consider here in the context of regression and cluster analysis, MoE usually use normal experts, that is, expert components following the Gaussian distribution. However, for a set of data containing a group or groups of observati...

This paper is concerned with the multivariate extended skew-normal [MESN] and skew-Student [MEST] distributions, that is, distributions in which location parameters of underlying truncated are not zero. The extra parameter leads to greater variability moments critical values, thus providing flexibility for empirical work. It reported this various theoretical properties notably limiting forms as...

The Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) type models have become important tools in financial application since their ability to estimate the volatility of time series data. In empirical literature, presence skewness and heavy-tails impacts on how well GARCH-type able capture market sufficiently. This study estimates asset returns based GARCH(1,1) model assuming Ske...

Recent literature discusses the persistence of skewness and tail risk in hedge fund returns. The aim of this paper is to suggest an alternative skewness measure  which is derived as the normalized shape parameter from the skew-normal distribution. First, we illustrate that the skew-normal distribution is better able to catch the characteristics of hedge fund returns than the normal distributio...

In many industrial experiments involving lifetimes of machines or units, experiments have to be terminated early or the number of experiments must be limited due to a variety of circumstances (e.g. when expensive, etc.) the samples that arise from such experiments are called censored data. Cohen (1991) was one of the earliest to study a more general censoring scheme called progressive censor...