View : 813 Download: 0
Modelling of Marginally Regular Bivariate Counting Process and its Application to Shock Model
- Title
- Modelling of Marginally Regular Bivariate Counting Process and its Application to Shock Model
- Authors
- Cha, Ji Hwan; Giorgio, Massimiliano
- Ewha Authors
- 차지환
- SCOPUS Author ID
- 차지환
- Issue Date
- 2018
- Journal Title
- METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY
- ISSN
- 1387-5841
1573-7713
- Citation
- METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY vol. 20, no. 4, pp. 1137 - 1154
- Keywords
- Reliability; Complete intensity functions; Dependence structure; Marginal process; Shock model; Primary 60K10; Secondary 62P30
- Publisher
- SPRINGER
- Indexed
- SCIE; SCOPUS
- Document Type
- Article
- 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.
- DOI
- 10.1007/s11009-018-9633-4
- Appears in Collections:
- 자연과학대학 > 통계학전공 > Journal papers
- Files in This Item:
There are no files associated with this item.
- Export
- RIS (EndNote)
- XLS (Excel)
- XML