Predictive analysis for joint progressive censoring plans: a Bayesian approach

Mohammad Vali Ahmadi and Mahdi Doostparast

Journal of Applied Statistics, 2022, vol. 49, issue 2, 394-410

Abstract: Comparative lifetime experiments are of particular importance in production processes when one wishes to determine the relative merits of several competing products with regard to their reliability. This paper confines itself to the data obtained by running a joint progressive Type-II censoring plan on samples in a combined manner. The problem of Bayesian predicting failure times of surviving units is discussed in details when parent populations are exponential. Two real data sets are analyzed in order to illustrate all the inferential procedures developed here. When destructive experiments under a censoring scheme finished, the researchers are usually interested to estimate remaining lifetimes of surviving units for sequel experiments. Findings of this paper are useful for these purposes specially when samples are non-homogeneous such as those taken from industrial storages.

Date: 2022
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DOI: 10.1080/02664763.2020.1815671

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