Bayesian estimation on interval censored Lindley distribution using Lindley’s approximation

Abstract

Interval censored data commonly arise in engineering and biomedical sciences. The present study deals with Bayesian estimation of interval censored lifetime data while it is assumed that lifetimes follow Lindley distribution. Assuming Jeffrey’s and gamma prior distributions, Bayes estimator of the Lindley parameter has been constructed under symmetric, squared error loss and asymmetric, general entropy loss functions. In addition, Bayes estimators for mean life, reliability and hazard rate have also been constructed. Since posterior distribution can not be reduced to any standard distribution, Lindley’s approximation technique has been utilized for Bayesian computations. The performances of the Bayes estimators has been compared with corresponding maximum likelihood estimators on the basis of simulated samples. Real data sets from engineering and biomedical fields have been analysed for illustration purposes. © 2016, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.