Modelling of Marginally Regular Bivariate Counting Process and its Application to Shock Model

Ji Hwan Cha, Massimiliano Giorgio

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper, we develop a new class of bivariate counting processes that have ‘marginal regularity’ property. But, the ‘pooled processes’ in the developed class of bivariate counting processes are not regular. Therefore, the proposed class of processes allows simultaneous occurrences of two types of events, which can be applicable in practical modeling of counting events. Initially, some basic properties of the new class of bivariate counting processes will be discussed. Based on the obtained properties, the joint distributions of the numbers of events in time intervals will be derived and the dependence structure of the bivariate process will be discussed. Furthermore, the marginal and conditional processes will be studied. The application of the proposed bivariate counting process to a shock model will also be considered. In addition, the generalization to the multivariate counting processes will be discussed briefly.

Original languageEnglish
Pages (from-to)1137-1154
Number of pages18
JournalMethodology and Computing in Applied Probability
Volume20
Issue number4
DOIs
StatePublished - 1 Dec 2018

Keywords

  • Complete intensity functions
  • Dependence structure
  • Marginal process
  • Reliability
  • Shock model

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