1. Bayesian Reliability: Combining Information
- Author
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Kassandra Fronczyk and Alyson G. Wilson
- Subjects
021103 operations research ,Computer science ,business.industry ,Bayesian probability ,0211 other engineering and technologies ,Inference ,Bayes factor ,02 engineering and technology ,Machine learning ,computer.software_genre ,01 natural sciences ,Industrial and Manufacturing Engineering ,Variable-order Bayesian network ,Bayesian statistics ,010104 statistics & probability ,Econometrics ,Feature (machine learning) ,Bayesian hierarchical modeling ,Artificial intelligence ,0101 mathematics ,Safety, Risk, Reliability and Quality ,business ,computer ,Reliability (statistics) - Abstract
One of the most powerful features of Bayesian analyses is the ability to combine multiple sources of information in a principled way to perform inference. This feature can be particularly valuable in assessing the reliability of systems where testing is..
- Published
- 2016
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