Estimators for the binomial failure rate common cause model

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Abstract
In Vesely's binomial failure rate model, a system of m components is hit by random shocks which may cause components simultaneously to fail, each component equal probability. Individual components may also fail when no shock has occurred. The data possibilities considered are that caused of single failures are identifiable (as shock or not) or not identifiable. Given data from such a system, non-Bayesian and Bayesian point and interval estimators are found for the various quantities of interest. Residual analyses and hypothesis tests are presented for checking the model assumptions. An example is worked out.

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