A theoretical expression is derived for the mean squared error of a nonparametric estimator of the tail dependence coefficient, depending on a threshold that defines which rank delimits the tails of a distribution. We propose a new method to optimally select this threshold. It combines the theoretical mean squared error of the estimator with a parametric estimation of the copula linking observations in the tails. Using simulations, we compare this semiparametric method with other approaches proposed in the literature, including the plateau-finding algorithm.

翻译：尾部依赖系数非对称估测符的平均正方形误差将产生理论表达式,这取决于界定分布的尾部界线的阈值。我们建议了一种新办法,以最佳方式选择这一阈值。它将估计符的理论平均正方形误差与将尾部观测结果连接在一起的千兆瓦的参数估测值结合起来。我们通过模拟,将这一半对称方法与文献中建议的其他方法,包括高原勘测算法进行比较。