Some results on change-point detection in cross-sectional dependence of multivariate data with changes in marginal distributions

被引：1

作者：

Rohmer, Tom ^{[1
,2
]}

机构：

[1] Univ Bordeaux, ISPED, 146 Rue Leo Saignat, F-33000 Bordeaux, France

[2] INSERM, Ctr Inserm U1219, 146 Rue Leo Saignat, F-33000 Bordeaux, France

来源：

STATISTICS & PROBABILITY LETTERS | 2016年 / 119卷

关键词：

Non-parametric tests; Sequential empirical copula process; Monte Carlo experiments; TIME-SERIES; TESTS;

D O I：

10.1016/j.spl.2016.06.026

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：

A non-parametric test is proposed for detecting changes in the dependence between the components of multivariate data, when changes in marginal distributions occur at known instants. Monte Carlo simulations have been carried out to illustrate the performance of the procedure. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：45 / 54

页数：10

共 13 条

[1]

[Anonymous], 2013, R LANG ENV STAT COMP

[2] WEAK-CONVERGENCE OF THE SEQUENTIAL EMPIRICAL PROCESSES OF RESIDUALS IN ARMA MODELS [J].