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

Name: A Generalized multivariate skew-normal distribution with applications to spatial and regression predictions
Brand: Vita e Pensiero
Availability: OnlineOnly

digital

Article

Magazine

STATISTICA & APPLICAZIONI

Section

Open Access

Title

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

Authors

Z.R. Al-Rawi, Mohd T. Alodat, T.T. Alodat

Publisher

Vita e Pensiero

Format

Article |

Pdf

Pages

Online from

02-2016

Issn

1824-6672 (print) | 2283-6659 (digital)

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Description Readers' comments

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.

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