On Bayesian Estimation in a Parallel System
Abstract This paper presents a Bayesian approach to the estimation of the reliability of a parallel system with k components. It is assumed that the strengths of the k components are subjected to a common stress which is independent of the strengths of the k components. The reliability of the parallel system or system reliability is estimated assuming that the strengths and the stress are exponentially distributed random variables. The performed Bayesian analysis is based on conjugated prior and non-informative prior distributions, respectively. A simulation data set is considered in order to study the performance of the Bayesian solutions. Some observations are discussed concerning alternative methods and possible extensions.
Year of publication: |
2006
|
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Authors: | Valdés, Gabriela A. ; Salinas, Víctor H. |
Published in: |
Stochastics and Quality Control. - Walter de Gruyter GmbH & Co. KG, ISSN 2367-2404, ZDB-ID 2905267-1. - Vol. 21.2006, 2, p. 231-242
|
Publisher: |
Walter de Gruyter GmbH & Co. KG |
Subject: | Failure time | Stress-Strength | Bayesian Reliability | Gibbs Sampling |
Saved in:
Online Resource
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