Smoothed jackknife empirical likelihood method for tail copulas

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.