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

Title
A new class of marginally regular multivariate counting processes generated by the mixture of multivariate Poisson processes
Authors
Cha J.H.Badía F.G.
Ewha Authors
차지환
SCOPUS Author ID
차지환scopus
Issue Date
2022
Journal Title
Communications in Statistics - Theory and Methods
ISSN
0361-0926JCR Link
Citation
Communications in Statistics - Theory and Methods vol. 51, no. 13, pp. 4235 - 4251
Keywords
complete intensity functionsdependence structureGeneralized Polya processmarginally regular multivariate counting process
Publisher
Taylor and Francis Ltd.
Indexed
SCIE; SCOPUS scopus
Document Type
Article
Abstract
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.
DOI
10.1080/03610926.2020.1812652
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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