Multivariate dependence concepts through copulas

被引：9

作者：

Wei, Zheng ^{[1
]}

Wang, Tonghui ^{[1
,2
]}

Nguyen, Phuong Anh ^{[3
]}

机构：

[1] New Mexico State Univ, Dept Math Sci, Las Cruces, NM 88003 USA

[2] Northwest A&F Univ, Coll Sci, Yangling, Peoples R China

[3] Int Univ Ho Chi Minh City, Ho Chi Minh City, Vietnam

来源：

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING | 2015年 / 65卷

关键词：

Affiliation; Copula; Linear interpolation; Positively quadrant dependent; Multivariate skew normal distribution; Affiliated signals; SKEW-NORMAL-DISTRIBUTION; 1ST-PRICE AUCTIONS; AFFILIATION;

D O I：

10.1016/j.ijar.2015.04.004

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, multivariate dependence concepts such as affiliation, association and positive lower orthant dependent are studied in terms of copulas. Relationships among these dependent concepts are obtained. An affiliation is a notion of dependence among the elements of a random vector. It has been shown that the affiliation property is preserved using linear interpolation of subcopula. Also our results are applied to the multivariate skew-normal copula. As an application, the dependence concepts used in auction with affiliated signals are discussed. Several examples are given for illustration of the main results. (C) 2015 Elsevier Inc. All rights reserved.

引用

页码：24 / 33

页数：10

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