In this chapter we review the fundamental concepts of Bayesian and likelihood-based inference in reliability. We explore prior distributions, sampling distributions, posterior distributions, and the relation between the three quantities as specified through Bayes’ Theorem. We also provide examples of inference in both discrete and continuous settings.
KeywordsPosterior Distribution Prior Distribution Bayesian Inference Launch Vehicle Prior Density
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