Markov modulated Bernoulli process

Süleyman Özekici

Mathematical Methods of Operations Research, 1997, vol. 45, issue 3, 324 pages

Abstract: We consider a Bernoulli process where the success probability changes with respect to a Markov chain. Such a model represents an interesting application of stochastic processes where the parameters are not constants; rather, they are stochastic processes themselves due to their dependence on a randomly changing environment. The model operates in a random environment depicted by a Markov chain so that the probability of success at each trial depends on the state of the environment. We will concentrate, in particular, on applications in reliability theory to motivate our model. The analysis will focus on transient as well as long-term behaviour of various processes involved. Copyright Physica-Verlag 1997

Keywords: Bernoulli Process; Markov Modulation; Transient Analysis; Ergodic Analysis (search for similar items in EconPapers)
Date: 1997
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1007/BF01194782 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:mathme:v:45:y:1997:i:3:p:311-324

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/00186

DOI: 10.1007/BF01194782

Access Statistics for this article

Mathematical Methods of Operations Research is currently edited by Oliver Stein

More articles in Mathematical Methods of Operations Research from Springer, Gesellschaft für Operations Research (GOR), Nederlands Genootschap voor Besliskunde (NGB)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().