Bayes computation for life testing and reliability estimation

Powerful computational techniques for estimating the parameters and the reliability function of complex life distributions, using Bayes methods, from complete and type-II censored samples are given. The Gibbs sampler approach brings considerable conceptual and computational simplicity to the calculation of the posterior marginals and reliability. Considering constrained parameter and truncated data problems in multivariate life distributions, the Gibbs sampler procedure is easy to implement for sets of simulated data. >

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