Statistical Inference for the Lomax Distribution under Progressively Type-II Censoring with Binomial Removal

This paper considers parameter estimations in Lomax distribution under progressive type-II censoring with random removals, assuming that the number of units removed at each failure time has a binomial distribution. The maximum likelihood estimators (MLEs) are derived using the expectation-maximization (EM) algorithm. The Bayes estimates of the parameters are obtained using both the squared error and the asymmetric loss functions based on the Lindley approximation. We compare the performance of our procedures using a simulation study and real data.