Volume 19, Issue 2 (12-2020)                   JIRSS 2020, 19(2): 119-131 | Back to browse issues page

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Darijani S, Zakerzadeh H, Torabi H. On the Canonical-Based Goodness-of-fit Tests for Multivariate Skew-Normality. JIRSS. 2020; 19 (2) :119-131
URL: http://jirss.irstat.ir/article-1-658-en.html
1Department of Statistics, Faculty of Mathematics, Yazd University, Iran. , saeed_darijani@yahoo.com
Abstract:   (1052 Views)

It is well-known that the skew-normal distribution can provide an alternative model to the normal distribution for analyzing asymmetric data. The aim of this paper is to propose two goodness-of-fit tests for assessing whether a sample comes from a multivariate skew-normal (MSN) distribution. We address the problem of multivariate skew-normality goodness-of-fit based on the empirical Laplace transform and empirical characteristic function, respectively, using the canonical form of the MSN distribution. Applications with Monte Carlo simulations and real-life data examples are reported to illustrate the usefulness of the new tests.

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Type of Study: Original Paper | Subject: 62Hxx: Multivariate analysis
Received: 2020/03/5 | Accepted: 2020/07/18 | Published: 2020/12/11

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