A Bayesian Approach for One-Shot Device Testing With Exponential Lifetimes Under Competing Risks


This paper considers a competing risk model for a 1-shot device testing analysis underneath an accelerated life check setting. Because of the consideration of competing risks, the joint posterior distribution becomes quite complicated. The Metropolis-Hastings sampling technique is used for the estimation of the posterior means that of the variables of interest. A simulation study is dispensed to assess the Bayesian approach with completely different priors, and additionally to check it with the EM algorithm for most chance estimation. Finally, an example from a tumorigenicity experiment is presented.

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