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.

中文翻译：

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在测量误差下进行校准

校准技术是使用辅助信息调整权重以更好地增强总体参数估计值的过程。在此手稿中，我们针对相关和不相关的测量误差下的总体均值提出了比率和回归类型的校准估计量。获得建议的校准估计量与一阶近似的方差，并比较它们的效率。进行了蒙特卡洛模拟研究，以显示测量误差对建议的校准估计量的影响。