Inference on Downton's Bivariate Exponential Distribution Based on Moving Extreme Ranked Set Sampling

The purpose of this paper is to estimate the parameters of Downton's bivariate exponential distribution using moving extreme ranked set sampling (MERSS). The estimators obtained are compared via their biases and mean square errors to their counterparts using simple random sampling (SRS). Monte Carlo simulations are used whenever analytical comparisons are difficult. It is shown that these estimators based on MERSS with a concomitant variable are more efficient than the corresponding ones using SRS. Also, MERSS with a concomitant variable is easier to use in practice than RSS with a concomitant variable. Furthermore, the best unbiased estimators among all unbiased linear combinations of the MERSS elements are derived for some parameters.