How to Deal with Tail Dependence of Mixture Copula with an Extreme Weight
摘要
Tail dependence is the tool to measure dependence in the extremes of a bivariate distribution. Copula is the function used to describe the dependence between the variables. Therefore, copula is used in order to determine the tail dependence. In this work, we focus on dealing with the case of an extreme weight of mixture copula. We provide the transformed Bayesian model averaging to estimate the tail dependence comparing with the conventional ways to estimate the mixture copula by simulation study.