A new class of ratio estimators under different sampling techniques

Abstract

This paper presents a novel approach to estimating the population mean by introducing a modified class of ratio estimators that effectively use auxiliary variables. Specifically, the coefficient of skewness (S_k) and quartile deviation (QD) are utilized within three distinct sampling methods: simple random sampling (SRS), ranked set sampling (RSS), and median ranked set sampling (MRSS). The estimators can improve accuracy and precision by incorporating these known auxiliary variables. The study investigates the estimators' mean square error (MSE) and bias, analyzing their performance up to the first degree of approximation. Through simulation and empirical studies, the results demonstrate the superior performance of the proposed estimators compared to existing methods.