On Type-II Hybrid Censored Lindley Distribution

Abstract

The present paper deals with the inferential study of Lindley distribution when the data are type-II hybrid censored. In classical set up, the maximum likelihood estimate of the parameter with its standard error are computed. Further, by assuming Jeffrey’s invariant and gamma priors for the unknown parameter, Bayes estimate along with its posterior standard error and highest posterior density credible interval of the parameter are obtained. Markov Chain Monte Carlo technique such as Metropolis-Hastings algorithm has been utilized to simulate draws from the posterior density of the parameter. Finally, a real data study is conducted for illustrative purpose.