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Bayesian Estimations Using MCMC Approach Under Three-Parameter Burr-XII Distribution Based on Unified Hybrid Censored Scheme

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Abstract

In this paper, we discussed the estimation of the unknown parameters in addition to survival and hazard functions for a three-parameter Burr-XII distribution based on unified hybrid censored data. The maximum likelihood and Bayes method have been used to obtain the estimating. The Fisher information matrix has been used to construct approximate confidence intervals. The Bayesian estimates for the unknown parameters have been obtained by Markov chain Monte Carlo (MCMC) method. Also, the credible intervals are constructed by using MCMC samples. Finally, we analyze a real data set to illustrate the proposed methods.

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Acknowledgements

The authors would like to express their thanks to the editor, the associate editor and the referees for their useful and valuable comments on improving the contents of this paper.

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Authors and Affiliations

  1. Mathematics Department, Faculty of Science, Al-Azhar University, Nasr City, Cairo, 11884, Egypt

    Rashad M. EL-Sagheer, Mohamed A. W. Mahmoud & Hasaballah M. Hasaballah

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  1. Rashad M. EL-Sagheer
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  2. Mohamed A. W. Mahmoud
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  3. Hasaballah M. Hasaballah
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Correspondence to Rashad M. EL-Sagheer.

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EL-Sagheer, R.M., Mahmoud, M.A.W. & Hasaballah, H.M. Bayesian Estimations Using MCMC Approach Under Three-Parameter Burr-XII Distribution Based on Unified Hybrid Censored Scheme. J Stat Theory Pract 13, 65 (2019). https://doi.org/10.1007/s42519-019-0066-3

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