A new class of marginally regular multivariate counting processes generated by the mixture of multivariate Poisson processes

被引:0
|
作者
Cha, Ji Hwan [1 ]
Badia, F. G. [2 ]
机构
[1] Ewha Womans Univ, Dept Stat, Seoul 120750, South Korea
[2] Univ Zaragoza, Dept Stat Methods, Zaragoza, Spain
基金
新加坡国家研究基金会;
关键词
Generalized Polya process; complete intensity functions; marginally regular multivariate counting process; dependence structure;
D O I
10.1080/03610926.2020.1812652
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper, a new class of marginally regular multivariate counting processes is developed and its stochastic properties are studied. The dependence of the proposed multivariate counting process is generated from two sources: by means of mixing and by sharing a common counting process. Even under a rather complex dependence structure, the stochastic properties of the multivariate process and its marginal processes are mathematically tractable. Initially, we define this multivariate counting process by means of mixing. For further characterization of it, we suggest an alternative definition, which facilitates convenient characterization of the proposed process. We derive the properties of the proposed multivariate counting process and analyze the multivariate dependence structure of the class.
引用
收藏
页码:4235 / 4251
页数:17
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