New Exponential Ratio Estimators using Auxiliary Information in Adaptive Cluster Sampling

Abstract

In this paper, two Exponential Ratio estimators using auxiliary information in Adaptive Cluster Sampling are proposed to estimate the finite population mean of the study variable. The estimators are proposed by using population coefficient of correlation and standard deviation of the auxiliary information. The expressions of biases and Mean Square Errors of the two proposed estimators are derived. A simulation study is also performed to reveal the efficiency of the two proposed estimators and compare with other estimators in Conventional Sampling and Adaptive Cluster Sampling. The proposed Ratio estimators are proved more efficient than the existing Ratio estimators both in Conventional Sampling and Adaptive Cluster Sampling.