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On the Bias of the Generalized Regression Estimator in Survey Sampling

机译:调查抽样中广义回归估计量的偏差

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摘要

It is well known that the generalized regression (GREG) estimator of the finite population total is asymptotically unbiased. Consequently, bias is negligible when the sample size is large. But the magnitude of the bias is not known, if we are estimating small areas or operating with small samples. Furthermore, beside the sample size, the bias depends on the auxiliary variables, on their relation to the study variable and on the sampling design. In small samples it is important to know sources of the bias and in some cases to use a bias-corrected regression estimator. The aim of the present paper is to derive approximate bias expressions of the GREG estimator under different population models and different sampling designs to study the magnitude of the bias.
机译:众所周知,有限总体总数的广义回归(GREG)估计量是渐近无偏的。因此,当样本量较大时,偏差可以忽略不计。但是,如果我们估计小面积或使用小样本,则偏差的大小未知。此外,除样本量外,偏差还取决于辅助变量,辅助变量与研究变量的关系以及抽样设计。在小样本中,了解偏差的来源很重要,在某些情况下,请使用偏差校正的回归估计量。本文的目的是在不同的人口模型和不同的抽样设计下,得出GREG估计量的近似偏差表达式,以研究偏差的大小。

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