Tests of multivariate copula exchangeability based on Lévy measures
本文提出检验随机向量Copula对称性的新方法，基于Copula特征函数和Lévy测度构建秩统计量，通过蒙特卡洛实验证明其比传统Cramér–von Mises检验更有效。
Abstract This paper introduces tests for the symmetry of the copula of random vector. The proposed statistics are based on the copula characteristic function and the weight function that appears naturally in their definition are assumed to belong to the general family of Lévy measures. The proposed test statistics are rank‐based and expresses as weighted ‐norms computed from a vector of empirical copula characteristic functions. Their nondegenerate asymptotic distributions under the null hypothesis and general alternatives, as well as the validity of a multiplier bootstrap for the computation of p ‐values, are derived using nonstandard arguments. Extended Monte–Carlo experiments show that the new tests hold their size well and are powerful against a wide range of alternatives, and appear to be more powerful than a Cramér–von Mises test based on empirical copulas.