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A Generalized multivariate skew-normal distribution with applications to spatial and regression predictions

digital A Generalized multivariate skew-normal distribution with
applications to spatial and regression predictions
Article
journal STATISTICA & APPLICAZIONI
issue STATISTICA & APPLICAZIONI - 2015 - 1
title A Generalized multivariate skew-normal distribution with applications to spatial and regression predictions
authors

publisher Vita e Pensiero
format Article | Pdf
online since 02-2016
issn 18246672 (print)
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In this paper, a generalization to the multivariate skew-normal distribution of Arnold and Beaver (2002) is proposed. Also several distributional properties of the proposed distribution are explored. The proposed distribution has been used to define a stochastic process called the generalized-skew Gaussian process. Furthermore, the paper focuses on applying the proposed distribution to two prediction problems namely, ordinary Kriging and Gaussian process for regression. It is shown that, if the sampling points of the generalized-skew Gaussian processes are chosen so that they are the vertices of a regular polygon, then the ordinary Kriging admit a uniformly best linear unbiased predictor. Finally, we re-analyzed the Gaussian process for regression model under the generalized-skew Gaussian process.