Type-II Progressively Censored Ranked Set Sampling

In this paper, the estimation of the exponential parameter via censored ranked set samples (RSS) is considered. Investigating optimal designs in the maximum likelihood estimation of exponential parameter via balanced ranked set sampling (BRSS) could be interesting. In this manuscript, a ranked set sampling design such as BRSS under progressively Type-II censoring is applied. Finally, via a Monte Carlo simulation study, some comparisons in terms of MSEs, biases and standard errors of proposed estimator have been made in this work. Then, the optimal censoring schemes can be discovered.