Bayesian Reliability Analysis
Bayesian reliability analysis estimates how long components or systems survive — their reliability, failure rate, and lifetime distribution — by combining observed (often censored) failure data with prior knowledge through Bayes' rule. As developed in Hamada, Wilson, Reese, and Martz's Bayesian Reliability (2008), it is especially valuable when failures are rare, tests are expensive, and engineering or historical information must be brought to bear.
Source record
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- Hamada, M. S., Wilson, A. G., Reese, C. S., & Martz, H. F. (2008). Bayesian Reliability. Springer Series in Statistics. Springer, New York. · DOI 10.1007/978-0-387-77950-8
- Hamada, M., Martz, H. F., Reese, C. S., Graves, T., Johnson, V., & Wilson, A. G. (2004). A fully Bayesian approach for combining multilevel failure information in fault tree quantification and optimal follow-on resource allocation. Reliability Engineering & System Safety, 86(3), 297–305. · DOI 10.1016/j.ress.2004.02.001
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