Titlebook: Bayesian Inference for Probabilistic Risk Assessment; A Practitioner‘s Gui Dana Kelly,Curtis Smith Book 2011 Springer-Verlag London Limited

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短程旅游

Bayesian Inference for Multilevel Fault Tree Models,nt (a “super-component”) and two sub-events (i.e., piece-parts). Also, we show how OpenBUGS can be used for the example models to estimate the probability of meeting a reliability goal at any level in the fault tree model.

大火

Additional Topics,prior distributions into OpenBUGS that are not included as predefined distribution choices. We close this chapter with an example of Bayesian inference for a time-dependent Markov model of pipe rupture.

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Paolo Becchi,Roberto Franzini Tibaldeoior distributions may be specified, including some cautions for developing an informative prior, and we introduce the concept of a Bayesian p-value for checking the predictions of the model against the observed data.

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內(nèi)行

https://doi.org/10.1007/978-1-84996-187-5Bayesian Inference; Bayesian Networks; CP6917; MCMC; Probabilistic Risk Assessment; Reliability; quality c

吸引人的花招

978-1-4471-2708-6Springer-Verlag London Limited 2011

BYRE

Time Trends for Binomial and Poisson Data,t λ in the binomial and Poisson distribution, respectively. This introduces new unknown parameters and makes the Bayesian inference significantly more complicated mathematically. However, modern tools such as OpenBUGS make this analysis no less tractable than the single-parameter cases analyzed earlier.

mechanism