ON A MULTIVARIATE GENERALIZED POLYA PROCESS without REGULARITY PROPERTY

Ji Hwan Cha, F. G. Badía

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Most of the multivariate counting processes studied in the literature are regular processes, which implies, ignoring the types of the events, the non-occurrence of multiple events. However, in practice, several different types of events may occur simultaneously. In this paper, a new class of multivariate counting processes which allow simultaneous occurrences of multiple types of events is suggested and its stochastic properties are studied. For the modeling of such kind of process, we rely on the tool of superposition of seed counting processes. It will be shown that the stochastic properties of the proposed class of multivariate counting processes are explicitly expressed. Furthermore, the marginal processes are also explicitly obtained. We analyze the multivariate dependence structure of the proposed class of counting processes.

Original languageEnglish
Pages (from-to)484-506
Number of pages23
JournalProbability in the Engineering and Informational Sciences
Volume34
Issue number4
DOIs
StatePublished - 1 Oct 2020

Keywords

  • characterization of multivariate counting processes
  • complete intensity functions
  • dependence structure
  • generalized polya process
  • superposition

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