m-Component Reliability Model in Bayesian Inference on Modified Weibull Distribution

Document Type : Original Research Article


Department of Statistics, Faculty of Science, Imam Khomeini International University, Qazvin, Iran


In order to produce more flexible models in the reliability theory field, the Bayesian inference of đť‘š-component reliability model with the non-identical-component strengths for modified Weibull distribution under the progressive censoring scheme is considered. One of the key benefits is the generality of this model, so it includes some cases studied previously, such as multi-component stress-strength model with one and two non-identical-component and stress-strength models. In addition, the study of progressive censored data discussed in this paper is critical in many practical situations. The problem is considered in three cases: when the two common parameters for strengths and stress variables are unknown, known, and general. In each case, the approximation methods, such as the MCMC and Lindley’s approximation, are used to consider the -component stress-strength parameter. The Monte Carlo simulation study compares the performance of different methods—finally, a demonstration of how the proposed model may be utilized to analyse real data sets.


Main Subjects

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