Multivariate Asymmetric Distributions of Copula Related Random Variables

It is known that normal distribution plays an important role in analysing symmetric data. However, this symmetric assumption may not hold in many real word and in such cases, asymmetric distribution, including skew normal distribution, are known as the best alternative. Constructing asymmetric d...

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Main Authors: Ayyub Sheikhi, Freshteh Arad, Radko Mesiar
Format: Article
Language:English
Published: Austrian Statistical Society 2023-07-01
Series:Austrian Journal of Statistics
Online Access:https://www.ajs.or.at/index.php/ajs/article/view/1446
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author Ayyub Sheikhi
Freshteh Arad
Radko Mesiar
author_facet Ayyub Sheikhi
Freshteh Arad
Radko Mesiar
author_sort Ayyub Sheikhi
collection DOAJ
description It is known that normal distribution plays an important role in analysing symmetric data. However, this symmetric assumption may not hold in many real word and in such cases, asymmetric distribution, including skew normal distribution, are known as the best alternative. Constructing asymmetric distributions is carried out using the conditional/selection approach of several independent variable conditioning on other set of variables and this approach does not work well when the independence between variables violated. In this work we construct an asymmetric distribution when variables are dependent using a copula. Specifically, we consider the random vectors X and Y are connected using a copula function CX,Y and we study the selection distribution Z = (X|Y ∈ T ). We present some special cases of our proposed distribution, among them, multivariate skew-normal distribution. Some properties such as moments and moment generating function are investigated. Also, numerical analysis including simulation study as well as a real data set analysis are presented for illustration.
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spelling doaj.art-2897e2220f7544f88a432a6c7a877fe12023-08-08T18:04:45ZengAustrian Statistical SocietyAustrian Journal of Statistics1026-597X2023-07-0152410.17713/ajs.v52i4.1446Multivariate Asymmetric Distributions of Copula Related Random VariablesAyyub Sheikhi0Freshteh AradRadko MesiarShahid BAhonar Univ of Kerman It is known that normal distribution plays an important role in analysing symmetric data. However, this symmetric assumption may not hold in many real word and in such cases, asymmetric distribution, including skew normal distribution, are known as the best alternative. Constructing asymmetric distributions is carried out using the conditional/selection approach of several independent variable conditioning on other set of variables and this approach does not work well when the independence between variables violated. In this work we construct an asymmetric distribution when variables are dependent using a copula. Specifically, we consider the random vectors X and Y are connected using a copula function CX,Y and we study the selection distribution Z = (X|Y ∈ T ). We present some special cases of our proposed distribution, among them, multivariate skew-normal distribution. Some properties such as moments and moment generating function are investigated. Also, numerical analysis including simulation study as well as a real data set analysis are presented for illustration. https://www.ajs.or.at/index.php/ajs/article/view/1446
spellingShingle Ayyub Sheikhi
Freshteh Arad
Radko Mesiar
Multivariate Asymmetric Distributions of Copula Related Random Variables
Austrian Journal of Statistics
title Multivariate Asymmetric Distributions of Copula Related Random Variables
title_full Multivariate Asymmetric Distributions of Copula Related Random Variables
title_fullStr Multivariate Asymmetric Distributions of Copula Related Random Variables
title_full_unstemmed Multivariate Asymmetric Distributions of Copula Related Random Variables
title_short Multivariate Asymmetric Distributions of Copula Related Random Variables
title_sort multivariate asymmetric distributions of copula related random variables
url https://www.ajs.or.at/index.php/ajs/article/view/1446
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AT freshteharad multivariateasymmetricdistributionsofcopularelatedrandomvariables
AT radkomesiar multivariateasymmetricdistributionsofcopularelatedrandomvariables