Inference for the generalized inverse Lindley distribution under type-II censored data

Abstract

In this paper, we consider the classical and the Bayesian inferences for the generalized inverse Lindley (GIL) distribution and their corresponding reliability characteristics (reliability function and hazard rate function) under the type-II censoring scheme. In the classical setup, first we obtain the maximum likelihood estimator for the unknown parameters of the distribution and their corresponding reliability characteristics. Further, we consider symmetric (squared error) and asymmetric (LINEX and general entropy) loss functions for the estimation of parameters and their corresponding reliability characteristics under the Bayesian paradigm. The performances of various derived estimators were recorded using Markov chain Monte Carlo (MCMC) simulation technique in Open BUGS for different sample sizes under type-II censoring schemes. Finally, a real data set is provided to illustrate the computation of various estimators.