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.
Original language | English |
---|---|
Pages (from-to) | 4235-4251 |
Number of pages | 17 |
Journal | Communications in Statistics - Theory and Methods |
Volume | 51 |
Issue number | 13 |
DOIs | |
State | Published - 2022 |
Bibliographical note
Publisher Copyright:© 2020 Taylor & Francis Group, LLC.
Keywords
- Generalized Polya process
- complete intensity functions
- dependence structure
- marginally regular multivariate counting process