Statistical Inference Using Progressively Type-II Censored Data with Random Scheme

Abstract

Statistical inference of an exponential distribution model, using progressively Type-II censored data with random scheme, is discussed in this paper. Maximum likelihood and Bayes procedures are used to derive both point and interval estimates of the parameters included in the model. Monte Carlo simulation method is used to generate a progressive Type-II censored data from exponential distribution, then these data is used to compute the point and interval estimations of the parameter and compare both the methods used when different random schemes.