Generalized exponential-type ratio-cum ratio estimators of population mean in ranked set and stratified ranked set sampling

Abstract

In this study, we propose generalized exponential type ratio-cum-ratio estimators of finite population mean using ranked Set Sampling (RSS) and stratified ranked set sampling (SRSS) schemes. The biases and Mean Square Errors (MSEs) of the proposed estimators are obtained up to first degree of approximation. Comparisons among the proposed and some existing estimators are made both theoretically and through simulation studies. Also, the estimators are compared in terms of relative bias (RB), relative mean square error (RRMSE) and percentage relative efficiency (PRE). It turned out that when the variable of interest and the auxiliary variables jointly follow a trivariate normal distribution, the proposed class of estimators of the population mean dominates all other competitor estimators.