On progressively censored generalized exponential distribution

In this paper, we consider the statistical inference of the unknown parameters of the generalized exponential distribution in presence of progressive censoring. We obtain maximum likelihood estimators of the unknown parameters using EM algorithm. We also compute the expected Fisher information matrix using the missing value principle. We then use these values to determine the optimal progressive censoring plans. Different optimality criteria are considered, and selected optimal progressive censoring plans are presented. One example has been provided for illustrative purposes.