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On Type-II Hybrid Censored two Parameter Rayleigh Distribution

Abhimanyu Singh Yadav, Min Yang


In life testing experiments, the most common censoring schemes are Type-I and Type-II censoring schemes. The hybrid censoring scheme is the mixture of Type-I and Type-II censoring scheme and presently has received considerable attention in the statistical literature. In this paper, we proposed the estimation of parameters of two Parameter Rayleigh distribution based on Type-II hybrid censored data. The maximum likelihood estimators and Bayes estimators are developed for estimating the unknown parameters. Bayes estimates of the parameter are obtained under suitable priors on the unknown parameters by using Lindley’s approximation and Markov Chain Monte Carlo techniques. Further, 95% asymptotic confidence and highest posterior density credible intervals for the unknown parameters are also obtained. We perform Monte Carlo simulations to compare the performances of the estimators obtained under different methods and finally, one real data set is analyzed for the illustrative purpose of the considered study.


Type-II Hybrid censoring, Classical and Bayesian estimation, Approximation techniques

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