A New Ratio Estimator in Stratified Adaptive Cluster Sampling

Abstract

Kadilar and Cingi considered the ratio estimators for the population mean of the variable of interest in stratified random sampling. In this paper we focus on the new ratio estimator (based on Kadilar and Cingi in stratified adaptive cluster sampling. Simulations showed the proposed estimator had the smallest estimated mean square error when compared to the ratio estimators in stratified sampling and the ratio estimator, based on Hansen-Hurwitz estimator, in stratified adaptive cluster sampling.