Prior Distributions Fitted to Observed Reliability Data
暂无分享,去创建一个
This paper describes methods of fitting prior distributions to equipment MTBF = ?, shows the priors fitted to different equipments, establishes data criteria for fitting prior distribution to ?, and presents the results of a robustness analysis performed on the fitted priors. Systematic procedures for fitting priors are shown for Type 1 data (number of failures in fixed time T) and Type 2 data (observed MTBF, number of failures not the same for all equipments), and specific data criteria, in the form of minimum values of n (number of equipments) and K (number of failures) are presented. The inverted-gamma prior-distributions were derived from operational failure data obtained from Tinker AFB. The equipments are primarily electronic, therefore, the time-to-failure distribution was assumed to be exponential; however, the methods are generally applicable whatever the form of the conditional distribution. The robustness analysis shows the effects of errors in estimating the parameters of the prior on the posterior distribution. In general, the effect of errors in estimating parameters of the prior was practically negligible for large values of K.
[1] Ingram Olkin,et al. Multivariate Correlation Models with Mixed Discrete and Continuous Variables , 1961 .
[2] H. Teicher. Identifiability of Mixtures , 1961 .
[3] R. G. Krutchkoff,et al. The empirical Bayes approach: estimating the prior distribution. , 1967, Biometrika.
[4] John E. Rolph,et al. Bayesian Estimation of Mixing Distributions , 1968 .