A new class of marginally regular multivariate counting processes generated by the mixture of multivariate Poisson processes
- 주제(키워드) complete intensity functions , dependence structure , Generalized Polya process , marginally regular multivariate counting process
- 등재 SCIE, SCOPUS
- 발행기관 Taylor and Francis Ltd.
- 발행년도 2022
- 총서유형 Journal
- URI http://www.dcollection.net/handler/ewha/000000193422
- 본문언어 영어
- Published As https://doi.org/10.1080/03610926.2020.1812652
초록/요약
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. © 2020 Taylor & Francis Group, LLC.
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