THE 2-STAGE BAYESIAN METHOD USED FOR THE T-BOOK APPLICATION

This paper presents a hierarchical or multistage empirical Bayesian ap proach that has been used for the estimation of uncertainty about comp onent failure rates presented in the T-Book, a handbook concerning rel iability data of components in Nordic nuclear power plants. The failur e process is basically assumed to be a homogeneous Poisson process. A class of contaminated gamma distributions is considered to describe th e uncertainty concerning the intensity of this process. These distribu tions in turn are defined through a set of hyperparameters, the knowle dge of which is also described and updated via Bayes formula. The prin ciple of Data Translated Likelihood is used for the derivation of non- informative prior distribution for the hyperparameters. The resulting Non-informative Contaminated Gamma-Poisson approach is illustrated by an example, the result of which is compared to alternative models. An application to a 2D problem is also presented.