Abstract
The calibration technique is the process of adjusting weights for the better enhancement of the estimate of the population parameters using auxiliary information. In this manuscript, we have proposed ratio and regression type calibration estimators for the population mean under both correlated and uncorrelated measurement errors. The variances of the proposed calibrated estimators to the first order approximation are obtained and compared their efficiencies. A Monte Carlo simulation study has been carried out to show the effect of measurement errors on the proposed calibrated estimators.
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