Parameter estimation of two-parameter Rayleigh distribution under progressive censoring with binomial removals

The estimation of unknown parameters of two-parameter Rayleigh distribution based on Type-II progressive censoring with binomial removals is studied. Maximum likelihood estimators of the parameters and their confidence intervals are derived. By applying Markov Chain Monte Carlo techniques, Bayes estimators, and corresponding highest posterior density confidence intervals of parameters are obtained. The expected time required to complete the life test under this censoring scheme is investigated. Monte Carlo simulations are performed to compare the performances of the different methods, and one data set is analyzed for illustrative purposes.