Bayesian Reliability Modeling Using Monte Carlo Integration
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May 1, 2005
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Vincent A. R. Camara
Department of Mathematics, University of South Florida
Chris P. Tsokos
Department of Mathematics, University of South Florida
Abstract
The aim of this article is to introduce the concept of Monte Carlo Integration in Bayesian estimation and Bayesian reliability analysis. Using the subject concept, approximate estimates of parameters and reliability functions are obtained for the three-parameter Weibull and the gamma failure models. Four different loss functions are used: square error, Higgins-Tsokos, Harris, and a logarithmic loss function proposed in this article. Relative efficiency is used to compare results obtained under the above mentioned loss functions
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