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Bayesian Prediction of Future Observations from Inverse Weibull Distribution Based on Type-II Hybrid Censored Sample

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Author(s): Sanjay Kumar Singh | Umesh Singh | Vikas Kumar Sharma

Journal: International Journal of Advanced Statistics and Probability
ISSN 2307-9045

Volume: 1;
Issue: 2;
Start page: 32;
Date: 2013;
Original page

ABSTRACT
In this paper, we have discussed the Bayesian procedure for the prediction of the future samples from inverse Weibull (IW) distribution under Type-II hybrid censoring scheme. Bayes estimators along with the corresponding highest posterior density (HPD) credible intervals have also been constructed for the parameters of IW distribution. The performance of the Bayes estimators of the model parameters has been compared with the maximum likelihood estimators through Monte Carlo Markov chain (MCMC) techniques. Finally, a real data set has been analyzed to illustrate the discussed methodology.
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