This chapter presents models for various types of component reliability data, which consist of sampling and prior distributions. Several examples with real data, including some for which the data are censored, illustrate the use of these models in assessing component reliability. The complexity of some of these examples requires the use of hierarchical models. This chapter also introduces methods for model selection.
KeywordsPosterior Distribution Markov Chain Monte Carlo Prior Distribution Bayesian Information Criterion Weibull Distribution
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