Bayesian Prediction Regions for the Extreme Order Statistics

In this paper, prediction bounds for the order statistics are dealt with. For this purpose, predictive distributions derived by Bayesian approach, are utilized. In particular, bounds for the smallest and the largest order statistics are set when a series of samples are drawn from exponential, Pareto and power function populations. These bounds assist in knowing the nature of these predicted statistics even without actually having the sample observations.