Generalized Exponential Ratio Type Estimator for the Finite Population Mean Under Ranked Set

In this study, we introduce a novel approach for estimating the mean of a finite population using Ranked Set Sampling (RSS), termed the generalized exponentialrtio a lrtio estimator. We derive expressions for the biasand mean squared error (MSE) of the proposed estimator up theto first order of approximation. To assess its performance, we conduct a thorough theoretical and numerical analysis using simulated and real data. Our results demonstrate that the generalized exponential ratio estimator outperforms both the classical ratio estimator ande thestimator proposed by Kadilar et al. (2009) under RSS, highlighting its superior efficienc