Inference Based on Sequential Order Statistics with Lindley Distribution

Abstract

In this paper, we consider the problem of estimation of parameters of Lindley distribution based on sequential order statistics under conditional proportional hazard rate model. Maximum Likelihood and Bayesian estimation techniques are applied for estimating the unknown parameters. Markov Chain Monte Carlo method is implemented for obtaining the Bayes estimators. An intensive simulation study is carried out to assess the performance of different estimators discussed in this paper. A real data analysis is also performed for illustrative purposes.