E-Bayesian Estimation Based on Burr-X Generalized Type-II Hybrid Censored Data

• Main Authors: Abdalla Rabie, Junping Li
• Format: Article
• Language: English
• Published: MDPI AG 2019-05-01
• Series: Symmetry
• Subjects: maximum likelihood estimation; Bayesian and E-Bayesian approaches; generalized hybrid censoring scheme; MCMC method; confidence and credible intervals
• Online Access: https://www.mdpi.com/2073-8994/11/5/626

In this article, we are concerned with the E-Bayesian (the expectation of Bayesian estimate) method, the maximum likelihood and the Bayesian estimation methods of the shape parameter, and the reliability function of one-parameter Burr-X distribution. A hybrid generalized Type-II censored sample from one-parameter Burr-X distribution is considered. The Bayesian and E-Bayesian approaches are studied under squared error and LINEX loss functions by using the Markov chain Monte Carlo method. Confidence intervals for maximum likelihood estimates, as well as credible intervals for the E-Bayesian and Bayesian estimates, are constructed. Furthermore, an example of real-life data is presented for the sake of the illustration. Finally, the performance of the E-Bayesian estimation method is studied then compared with the performance of the Bayesian and maximum likelihood methods.