Copula-based conditional tail indices

被引:2
|
作者
Coia, Vincenzo [1 ]
Joe, Harry [2 ]
Nolde, Natalia [2 ]
机构
[1] BGC Engn, Vancouver, BC, Canada
[2] Univ British Columbia, Dept Stat, Vancouver, BC, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Conditional distribution; Copula; Regular variation; Tail index; Vine;
D O I
10.1016/j.jmva.2023.105268
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Consider a multivariate distribution of (X, Y), where X is a vector of predictor variables and Y is a response variable. Results are obtained for comparing the conditional and marginal tail indices, eY|X(x) and eY, based on conditional distributions {FY|X(& sdot;|x)} and marginal distribution FY, respectively. For a multivariate distribution based on a copula, the conditional tail index can be decomposed into a product of copula -based conditional tail indices and the marginal tail index. In some applications, one may want eY|X(x) to be non -constant, and some new copula families are derived to facilitate this.
引用
收藏
页数:14
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