Analysis of Weibull Distribution Under Adaptive Type-II Progressive Hybrid Censoring Scheme
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This paper is an effort to obtain the maximum likelihood and the Bayes estimators for the unknown parameters of the Weibull distribution based on adaptive type-II progressive hybrid censoring scheme. The Bayes estimates of the unknown parameters are obtained with respect to symmetric loss function (squared error loss) and asymmetric loss function (LINEX loss) under the assumption of independent gamma priors. The Lindley’s approximation and the Monte Carlo Markov chain techniques have been utilized for Bayesian calculation. Also, the asymptotic confidence intervals, two parametric bootstrap confidence intervals using frequentist approaches are provided to compare with Bayes credible intervals. To evaluate the performance of the estimators, a simulation study is carried out. Finally, a real life data set have been analyzed for illustrative purposes. Finally, we discuss a method of obtaining the optimal adaptive progressive hybrid censoring scheme.
KeywordsWeibull distribution Adaptive type-II progressive hybrid censoring Maximum likelihood estimation Bayesian estimation Lindley approximation
The authors would like to thank the referee, Editor-in-Chief and Associate Editor for careful reading and for comments which greatly improved the paper.
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