Title: E-Bayesian estimation for Burr-X distribution based on Type-II hybrid censoring scheme

Authors: Abdalla Rabie; Junping Li

Addresses: School of Mathematics and Statistics, Central South University, Changsha, Hunan 410083, China; Department of Mathematics, Faculty of Science, Al-Azhar University, Assiut 71524, Egypt ' School of Mathematics and Statistics, Central South University, Changsha, Hunan 410083, China

Abstract: In this paper, Burr-X distribution with Type-II hybrid censored data is considered. The E-Bayesian estimation (the expectation of the Bayesian estimate) and the corresponding Bayesian and maximum likelihood estimation methods are studied for the distribution parameter and the reliability function. Bayesian and E-Bayesian estimates are obtained under LINEX and squared error loss functions. By applying the Markov chain Monte Carlo techniques, Bayesian and E-Bayesian estimates are obtained. Also, confidence intervals of maximum likelihood estimates, as well as credible intervals of Bayesian and E-Bayesian estimates, are constructed. Furthermore, a numerical example of a real-life dataset is provided for the purpose of illustration. Finally, a comparison among the E-Bayesian, the Bayesian and the maximum likelihood methods is presented.

Keywords: Bayesian estimation; E-Bayesian estimation; maximum likelihood estimation; hybrid censoring scheme; confidence interval; credible interval; MCMC method.

DOI: 10.1504/IJCSM.2021.119899

International Journal of Computing Science and Mathematics, 2021 Vol.14 No.3, pp.233 - 248

Received: 21 Feb 2019
Accepted: 04 Apr 2019
Published online: 23 Dec 2021 *

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