BAYESIAN ESTIMATION AND PREDICTION BASED ON EXPONENTIAL RESIDUAL TYPE II CENSORED LIFE DATA

Abstract

In this paper, we consider statistical inference problems for the residual life data come from exponential model based on type II censored data.  Maximum likelihood and Bayesian approaches are used to estimate the scale parameter for exponential model also we construct symmetric credible intervals.  Further, we propose to estimate the posterior predictive density of the future ordered observations and then obtain the corresponding predictors and we obtain the predictive survival function to compute the predictive interval for the missing order statistics.  Numerical comparisons are conducted to assess the performance of the estimators of the parameter as well as the predictors of future ordered data.