Copulas are used to depict dependence among several random variables. Both parametric and non-parametric estimation methods have been studied in the literature. Moreover, profile empirical likelihood methods based on either empirical copula estimation or smoothed copula estimation have been proposed to construct confidence intervals of a copula. In this paper, a jackknife empirical likelihood method is proposed to reduce the computation with respect to the existing profile empirical likelihood methods.
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Acknowledgements We thank two reviewers for their helpful comments. Peng’s research was supported by NSA grant H98230-10-1-0170 and NSF grant DMS1005336. Qi’s research was supported by NSA grant H98230-10-1-0161 and NSF grant DMS1005345. Ingrid Van Keilegom acknowledges financial support from IAP research network P6/03 of the Belgian Government (Belgian Science Policy), and from the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement No. 203650.
- Empirical likelihood method