Estimating the entropy of a Weibull distribution under generalized progressive hybrid censoring

Abstract

Recently, progressive hybrid censoring schemes have become quite popular ina life-testing problem and reliability analysis. However, the limitation of the progressivehybrid censoring scheme is that it cannot be applied when few failures occur before time T.Therefore, a generalized progressive hybrid censoring scheme was introduced. In thispaper, the estimation of the entropy of a two-parameter Weibull distribution based on thegeneralized progressively censored sample has been considered. The Bayes estimatorsfor the entropy of the Weibull distribution based on the symmetric and asymmetric lossfunctions, such as the squared error, linex and general entropy loss functions, are provided.The Bayes estimators cannot be obtained explicitly, and Lindley's approximation is used toobtain the Bayes estimators. Simulation experiments are performed to see the effectivenessof the different estimators. Finally, a real dataset has been analyzed for illustrative purposes.