Estimation Based on Progressively Censored Data from Weibull-Exponential Distribution

Abstract

In this paper, Weibull-exponential distribution is considered which is capable of modeling various shapes of failure rates and ageing criteria. The maximum likelihood estimates of unknown parameters and reliability characteristic are obtained. Approximate interval estimates are also constructed using asymptotic distributions of maximum likelihood estimates. Bayes estimates are derived under the squared error loss function. These estimators can not be obtained in explicit form when all parameters are unknown. So we have used Lindley’s approximation and Metropolis–Hastings algorithm to obtain Bayes estimates. We also obtain highest posterior density credible intervals of unknown parameters. A numerical study is performed to compare the proposed estimates using simulations. Two real data sets are analyzed for the illustration purposes.