Bayesian analysis of Markov Modulated Bernoulli Processes

S. Özekici and R. Soyer

Mathematical Methods of Operations Research, 2003, vol. 57, issue 1, 125-140

Abstract: We consider Markov Modulated Bernoulli Processes (MMBP) where the success probability of a Bernoulli process evolves over time according to a Markov chain. The MMBP is applied in reliability modeling where systems and components function in a randomly changing environment. Some of these applications include, but are not limited to, reliability assessment in power systems that are subject to fluctuating weather conditions over time and reliability growth processes that are subject to design changes over time. We develop a general setup for analysis of MMBPs with a focus on reliability modeling and present Bayesian analysis of failure data and illustrate how reliability predictions can be obtained. Copyright Springer-Verlag Berlin Heidelberg 2003

Keywords: Key words: Markov modulation; Bernoulli process; System reliability; Bayesian analysis (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:mathme:v:57:y:2003:i:1:p:125-140

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DOI: 10.1007/s001860200268

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