The Notion of “Composite Reliability” and its Hierarchical Bayes Estimation
本文提出“复合可靠性”概念，用于衡量一组异质但相似项目的整体可靠性，并开发了分层贝叶斯模型来估计系统可靠性，适用于小比例二项参数的同时推断。
Abstract In this article we introduce the notion of “composite reliability” as a measure of the overall reliability of a collection of heterogeneous but similar items. We then propose a hierarchical Bayes model for estimating the composite reliability of systems whose lifelengths are expressed as binary random variables. Subsequently, we develop an alternative approach for the simultaneous inference about many small but related binomial parameters. We propose a two-stage prior for addressing problems of this type and use the Gibbs sampler algorithm for addressing problems involving small proportions. Our topic, though suggested by an issue pertaining to the safety of nuclear power plants, arises in other commonly occurring situations pertaining to consumerism, public policy government regulation. Our development generalizes for situations involving lifelengths that need not be binary.