Multivariate extension of Raftery copula

• Main Authors: Saali, Tariq, Mhamed. Mesfioui, Mhamed. Mesfioui, Shabri, Ani
• 格式: Article
• 語言: English
• 出版: MDPI 2023
• 主題: QA Mathematics
• 在線閱讀: http://eprints.utm.my/105664/1/TariqSaali2023_MultivariateExtensionofRafteryCopula.pdf; http://eprints.utm.my/105664/; http://dx.doi.org/10.3390/math11020414

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