Multivariate Extension of Raftery Copula

This paper introduces a multivariate extension of Raftery copula. The proposed copula is exchangeable and expressed in terms order statistics. Several properties this are established. In particular, the Kendall’s tau Spearman’s rho, as well density function, suggested derived. lower upper tail dependence also parameter estimator new examined based on maximum likelihood procedure. A simulation study shows satisfactory performance presented estimator. Finally, successfully applied to real data set black cherry trees.