Efficiently sampling exchangeable Cuadras-Augé copulas in high dimensions

We construct an n-dimensional random vector whose survival copula is given by a copula function that was first presented in Cuadras, Auge (1981). Our construction adds a Poisson subordinator as mixing variable to initially independent exponentially distributed random variables. We show how the parameters of the Poisson process relate to the parameter of the induced Cuadras-Auge copula. Based on this construction, we present a sampling algorithm for this multivariate distribution which has average computational efficiency O(n log log n).     «

We construct an n-dimensional random vector whose survival copula is given by a copula function that was first presented in Cuadras, Auge (1981). Our construction adds a Poisson subordinator as mixing variable to initially independent exponentially distributed random variables. We show how the parameters of the Poisson process relate to the parameter of the induced Cuadras-Auge copula. Based on this construction, we present a sampling algorithm for this multivariate distribution which has averag...     »