Inference of Progressively Censored Data from The Generalized Exponential Distribution

In this paper, we derive approximate moments of progressively type-II right censored order statistics from the generalized exponential distribution . Also, using these moments to derive the best linear unbiased estimates and maximum likelihood estimates of the location and scale parameters from the generalized exponential distribution. In addition, we use Monte-Carlo simulation method to obtain the mean square error of the best linear unbiased estimates and maximum likelihood estimates and make comparison between them. Finally, we will present numerical example to illustrate the inference procedures developed in this distribution.