Bayesian Analysis of Reliability-growth Test for Exponential Life Distribution Case Based on a New Dirichlet Prior Distribution
This article researches a new method for the application of bayesian theory to the reliability-growth for Exponential distribution. Aiming at some history and expert information during the development of a motor, a Bayesian reliability growth model was presented based on the New Dirichlet distribution. Bayesian point assessment and confidence lower limit on product reliability at current stage are imputed by comprehensively making use of prior information and field test information at each stage. The method for determining prior distribution parameters was given by the method of optimization, it is easy to confirm the parameters of prior distribution, it solves the problem of how to verify the hyper parameters of the new Dirichlet prior distribution because of these parameters having no specific physical meaning. The Gibbs sampling algorithm was used to solve the problem that interference on parameters of Bayesian posterior higher dimensions cant calculate indirectly, and the numerical simulation is used for this model. The analysis result of practical cases proves the objectivity and validity of the model.
Reliability growth Bayesian analysis New Dirichlet distribution Exponential distribution MCMC simulation Gibbs sampling
MING Zhimao TAOJunyong ZHANG Yunan CHEN Xun
College of Mechatronics Engineering and Automation.National University of Defense Technology,Changsh College of Mechatronics Engineering and Automation,National University of Defense Technology,Changsh
国际会议
2008 International Conference on Risk and Relianility Management(2008风险与可靠性管理国际会议)
北京
英文
669-673
2008-11-10（万方平台首次上网日期，不代表论文的发表时间）