E-Bayesian estimation of Burr Type XII model based on adaptive Type-II progressive hybrid censored data

In this paper, we obtain the E-Bayesian estimation of the parameter and the reliability function of the Burr type-XII distribution under adaptive progressive Type-II censoring scheme. The E-Bayesian estimation is investigated using three different prior distributions based on squared error and LINEX loss functions. The properties of the E-Bayesian estimation and the E-posterior risk under squared error and LINEX loss functions are also discussed. An extensive simulation study is conducted to compare the behaviour of the E-Bayesian estimation with the corresponding Bayes and maximum likelihood estimators. We analyze one real data set to show the applicability of the different estimators in practice.

Automated summary

This paper investigates the E-Bayesian estimation of the parameter and reliability function of the Burr type-XII distribution under adaptive progressive Type-II censoring scheme, using three different prior distributions and discussing properties under squared error and LINEX loss functions. An extensive simulation study compares the E-Bayesian estimation with Bayes and maximum likelihood estimators, and a real data set analysis demonstrates the applicability of different estimators in practice.