Some applications of the strong approximation of the integrated empirical copula processes
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- 作者：S. Bouzebda
- 关键词：multivariate empirical copula processes ; strong invariance principles ; Kiefer processes ; Gaussian processes ; change ; point detection
- 刊名：Mathematical Methods of Statistics
- 出版年：2016
- 出版时间：October 2016
- 年：2016
- 卷：25
- 期：4
- 页码：281-303
- 全文大小：
- 刊物类别：Mathematics and Statistics
- 刊物主题：Statistical Theory and Methods;
- 出版者：Allerton Press
- ISSN：1934-8045
- 卷排序：25
文摘
The purpose of the present paper is to provide a strong invariance principle for the integrated empirical copula process [introduced in a series of papers by Henze and Nikitin in the univariate setting] with the rate of the approximation for multivariate empirical processes. The applications discussed here are change-point detection in multivariate copula models and the integrated empirical copula process with estimated parameter. Finally, a general notion of bootstrapped integrated empirical copula process, constructed by exchangeably weighting sample, is presented.