Improved predictive estimation for mean using the Searls technique under ranked set sampling

This manuscript presents the extended and improved form of the predictive estimation of the population mean under the ranked set sampling (RSS). We have extended the predictive estimation using "ratio and product" exponential estimators of Bahl and Tuteja as predictors under RSS, and the resulting predictive estimators differ from the usual "ratio and product" exponential estimator under RSS. Further, we have developed proposed improved predictive estimators using the Searls technique under RSS corresponding to customary predictive estimators under RSS. The expression for the biases and MSEs of the proposed improved estimators are obtained up to the first-order of approximation. Efficiency comparisons, simulation and empirical study illustrate the superiority of our proposed estimators under RSS.