Bayesian estimation and prediction for the generalized Lindley distribution under asymmetric loss function

Abstract

The paper develops the Bayesian estimation procedure for the generalized Lindley distribution under squared error and general entropy lossfunctions in case of complete sample of observations. For obtaining theBayes estimates, both non-informative and informative priors are used.Monte Carlo simulation is performed to compare the behaviour of theproposed estimators with the maximum likelihood estimators in termsof their estimated risks. Discussion is further extended to Bayesianprediction problem based on an informative sample where an attemptis made to derive the prediction intervals for future observations.Numerical illustrations are provided based on a real data example.