Comparison of Estimators in Case of Low Correlation in Adaptive Cluster Sampling

Abstract

In this paper, two Regression-Cum-Exponential Estimators have been proposed to estimate the population mean using population mean of single auxiliary variable in Adaptive Cluster Sampling. The expressions for the Mean Square Error and Bias of the proposed Estimators have been derived. A simulation study has been carried out to demonstrate and compare the efficiencies and precisions of the Estimators. The proposed Estimators have been compared with Ratio, Regression, Exponential Ratio Estimators in usual sampling, the Hansen-Hurwitz and the Ratio Estimators in Adaptive Cluster Sampling when there is low positive correlation between study variable and auxiliary variable.