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Bayesian \(C\)-optimal life testing plans under progressive type-I interval censoring scheme. (English) Zbl 1464.62410

Summary: This work considers optimal planning of progressive type-I interval censoring schemes for log-location-scale family of distributions. Optimum schemes are obtained by using a Bayesian \(C\)-optimality design criterion. The \(C\)-optimality criterion is formed to attain precision in estimating a particular lifetime quantile. An algorithm is proposed to obtain the optimal censoring schemes. Optimal schemes are obtained under two different scenarios for the Weibull and log-normal models, which are two popular special cases of log-location-scale family of distributions. A sensitivity analysis is conducted to study the effect of various prior inputs on the optimal censoring schemes. Furthermore, a simulation study is undertaken to illustrate the sampling variations resulting from the optimal censoring schemes.

MSC:

62N05 Reliability and life testing
62N01 Censored data models
62F15 Bayesian inference

Software:

SPLIDA
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References:

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