Dependent Lindeberg central limit theorem for the fidis of empirical processes of cluster functionals

被引:1
|
作者
Gomez, Jose G. [1 ,2 ]
机构
[1] Univ Cergy Pontoise, Dept Math, F-95000 Cergy Pontoise, France
[2] Univ Paris 13, Dept Math, Inst Galilee, F-93430 Villetaneuse, France
关键词
Clustering of extremes; cluster functional; extremogram; central limit theorem; Lindeberg method; weak dependence; MULTIVARIATE NORMALITY; WEAK DEPENDENCE; EXTREMOGRAM;
D O I
10.1080/02331888.2018.1470630
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
Drees H. and Rootzen H. [Limit theorems for empirical processes of cluster functionals (EPCF). Ann Stat. 2010;38(4):2145-2186] have proven central limit theorems (CLTs) for EPCF built from beta-mixing processes. However, this family of beta-mixing processes is quite restrictive. We expand some of those results, for the finite-dimensional marginal distributions (fidis), to a more general dependent processes family, known as weakly dependent processes in the sense of Doukhan P. and Louhichi S. [A new weak dependence condition and applications to moment inequalities. Stoch. Proc. Appl. 1999;84:313-342]. In this context, the CLT for the fidis of EPCF is sufficient in some applications. For instance, we prove the convergence without mixing conditions of the extremogram estimator, including a small example with simulation of the extremogram of a weakly dependent random process but nonmixing, in order to confirm the efficacy of our result.
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页码:955 / 979
页数:25
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