Smoothed jackknife empirical likelihood method for tail copulas

Liang Peng, Yongcheng Qi

Research output: Contribution to journalArticle

9 Citations (Scopus)

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 languageEnglish (US)
Pages (from-to)514-536
Number of pages23
JournalTest
Volume19
Issue number3
DOIs
StatePublished - Nov 1 2010

Fingerprint

Jackknife
Empirical Likelihood
Likelihood Methods
Copula
Tail
Likelihood Ratio Statistic
Wilks' Theorem
Dependence Function
Tail Dependence
Bootstrap Method
Confidence interval
Extremes
Simulation Study
Empirical likelihood
Likelihood ratio statistic

Keywords

  • Confidence interval
  • Empirical likelihood
  • Jackknife
  • Tail copula

Cite this

Smoothed jackknife empirical likelihood method for tail copulas. / Peng, Liang; Qi, Yongcheng.

In: Test, Vol. 19, No. 3, 01.11.2010, p. 514-536.

Research output: Contribution to journalArticle

Peng, Liang ; Qi, Yongcheng. / Smoothed jackknife empirical likelihood method for tail copulas. In: Test. 2010 ; Vol. 19, No. 3. pp. 514-536.
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