Point and Interval Estimation of Reliability and Entropy for Generalized Exponential Distribution under Generalized Type-II Hybrid Censoring Scheme

In this research paper, the estimation of reliability and entropy measures are analyzed within the context of a generalized Type-II hybrid censoring scheme (GT2HCS) The analysis is conducted while considering a generalized exponential distribution as the underlying lifetime distribution. The study specifically emphasizes the calculation of both Shannon and Renyi entropy measures. Maximum likelihood estimation is evaluated for estimating reliability and entropy measures, along with their asymptotic confidence intervals. Bayesian estimation techniques are also considered, utilizing gamma priors for unknown parameters under different loss function. Markov Chain Monte Carlo technique is employed using Metropolis-Hasting algorithm for obtaining Bayesian estimates. Furthermore, credible intervals are determined using the highest posterior density approach. Monte Carlo simulation study is conducted to assess the performance of the proposed estimators. Additionally, a real-life data set from an engineering application is analyzed to demonstrate the GT2HCS under different estimation methods proposed in the study.