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New improved calibration estimator based on two auxiliary variables in stratified two-phase sampling

机译:基于两个辅助变量在分层两相抽样中的新改进校准估计

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This paper considers the problem of estimating the population mean of the study variable when auxiliary information is not available and proposes new calibration approach alternative to the recent existing calibration estimators for estimating population mean of the study variable using two auxiliary variables in stratified two-phase sampling. The theory of new calibration estimation is given and optimum weights are derived under two-phase sampling approach. A simulation study is carried out to performance of the proposed calibration estimator with other existing calibration estimators. The results demonstrate that the proposed calibration estimator is more efficient than other existing calibration estimators of the population mean in stratified two-phase sampling.
机译:本文考虑估计研究变量的人口平均值的问题,当辅助信息不可用,并提出新的校准方法替代最近的现有校准估计值,用于使用两个辅助变量在分层的两相抽样中使用两个辅助变量估算研究变量的群体平均值。给出了新的校准估计理论,并且在两相采样方法下导出了最佳权重。对具有其他现有校准估计器的建议校准估计器进行仿真研究。结果表明,所提出的校准估计器比分层两相抽样中的群体的其他现有校准估计更有效。

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