Calibrated estimators using non-linear calibration constraints

Abstract

ABSTRACTIn this paper, the problem of estimation of mean through calibration technique has been discussed. In the current investigation, we proposed new calibrated estimators of mean in simple random sampling, probability proportional to size sampling and stratified random sampling by considering non-linear constraints of an auxiliary variable. It has been shown through simulation study that the resultant estimators are more efficient than the combined regression as well as the combined ratio estimator in all three sampling designs.