Abstract
In this paper we propose a smoothed jackknife empirical likelihood method to construct confidence intervals for tail copulas or tail dependence functions for bivariate extremes. By applying the standard empirical likelihood method for a mean to the smoothed jackknife sample, the empirical likelihood ratio statistic can be calculated by simply solving a single equation. Therefore, this procedure is easy to implement. The Wilks' theorem for the empirical likelihood ratio statistic is proved, and a simulation study prefers the proposed method to the bootstrap method.
Original language | English (US) |
---|---|
Pages (from-to) | 514-536 |
Number of pages | 23 |
Journal | Test |
Volume | 19 |
Issue number | 3 |
DOIs | |
State | Published - Nov 2010 |
Bibliographical note
Funding Information:Acknowledgements We thank three reviewers for their helpful comments. Peng’s research was supported by NSA grant H98230-10-1-0170 and Qi’s research was supported by NSA grant H98230-10-1-0161.
Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
Keywords
- Confidence interval
- Empirical likelihood
- Jackknife
- Tail copula