On some efficient logarithmic type estimators under stratified ranked set sampling

This paper investigates the performance of combined and separate log type class of estimators of population mean under stratified ranked set sampling. The expressions of bias and mean square error of the proposed estimators are deduced. The theoretical comparison of the proposed estimators with the existing estimators is carried out and the efficiency conditions are reported. The credibility of theoretical results is extended by a simulation study conducted over various artificially generated symmetric and asymmetric populations. The results of the simulation study show that the proposed class of estimators dominate the well-known existing estimators.