Jackknife empirical likelihood for parametric copulas

Ruodu Wang, Liang Peng and Jingping Yang

Scandinavian Actuarial Journal, 2013, vol. 2013, issue 5, 325-339

Abstract: For fitting a parametric copula to multivariate data, a popular way is to employ the so-called pseudo maximum likelihood estimation proposed by Genest, Ghoudi, and Rivest. Although interval estimation can be obtained via estimating the asymptotic covariance of the pseudo maximum likelihood estimation, we propose a jackknife empirical likelihood method to construct confidence regions for the parameters without estimating any additional quantities such as the asymptotic covariance. A simulation study shows the advantages of the new method in case of strong dependence or having more than one parameter involved.

Date: 2013
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DOI: 10.1080/03461238.2011.611893

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