TY - JOUR
T1 - A new class of marginally regular multivariate counting processes generated by the mixture of multivariate Poisson processes
AU - Cha, Ji Hwan
AU - Badía, F. G.
N1 - Funding Information:
The work of the first author was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (Grant Number: 2019R1A6A1A11051177). The authors greatly thank the Associate Editor and the referee for helpful comments and advices, which have improved the presentation of this paper. The work of the second author has been supported by the Spanish government research projects MTM2015-63978 (MINECO-FEDER) and PGC2018-094964- B-100 (MINECO-FEDER).
Funding Information:
The authors greatly thank the Associate Editor and the referee for helpful comments and advices, which have improved the presentation of this paper. The work of the second author has been supported by the Spanish government research projects MTM2015-63978 (MINECO-FEDER) and PGC2018-094964- B-100 (MINECO-FEDER).
Publisher Copyright:
© 2020 Taylor & Francis Group, LLC.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - Generalized Polya process
KW - complete intensity functions
KW - dependence structure
KW - marginally regular multivariate counting process
UR - http://www.scopus.com/inward/record.url?scp=85090128606&partnerID=8YFLogxK
U2 - 10.1080/03610926.2020.1812652
DO - 10.1080/03610926.2020.1812652
M3 - Article
AN - SCOPUS:85090128606
SN - 0361-0926
VL - 51
SP - 4235
EP - 4251
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
IS - 13
ER -