Dependence and mixing for perturbations of copula-based Markov chains

被引：3
|
作者：
Longla, Martial [1 ]
Nthiani, Mathias Muia [1 ]
Ndikwa, Fidel Djongreba [2 ]
机构：
[1] Univ Mississippi, Dept Math, University, MS 38677 USA
[2] Univ Maroua, Dept Math, Maroua, Cameroon
来源：
STATISTICS & PROBABILITY LETTERS | 2022年 / 180卷
关键词：
Perturbation; Central limit theorem; Copulas; Mixing rates; Dependence coefficients;
D O I：
10.1016/j.spl.2021.109239
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：
This paper explores the impact of perturbations of copulas on dependence properties of the Markov chains they generate. We use an observation that is valid for convex combinations of copulas to establish sufficient conditions for the mixing coefficients rho(n), alpha(n) and some other measures of association. New copula families are derived based on perturbations of copulas and their multivariate analogs for n-copulas are provided in general. Several families of copulas can be constructed from the provided framework. (C) 2021 Elsevier B.V. All rights reserved.
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页数：8
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