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On combining independent probability samples

机译:关于组合独立概率样本

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Merging available sources of information is becoming increasingly important for improving estimates of population characteristics in a variety of fields. In presence of several independent probability samples from a finite population we investigate options for a combined estimator of the population total, based on either a linear combination of the separate estimators or on the combined sample approach. A linear combination estimator based on estimated variances can be biased as the separate estimators of the population total can be highly correlated to their respective variance estimators. We illustrate the possibility to use the combined sample to estimate the variances of the separate estimators, which results in general pooled variance estimators. These pooled variance estimators use all available information and have potential to significantly reduce bias of a linear combination of separate estimators.
机译:合并可用的信息源对于改善各个领域的人口特征估计变得越来越重要。在存在来自有限总体的几个独立概率样本的情况下,我们将基于单独估计量的线性组合或基于组合样本的方法,研究总体总数的组合估计量的选项。基于总体差异的线性组合估算器可能会出现偏差,因为总体总数的单独估算器可能与它们各自的方差估算器高度相关。我们说明了使用组合样本来估计单独估计量的方差的可能性,这导致了一般合并方差估计量。这些合并的方差估计量会使用所有可用信息,并有可能显着降低单独估计量的线性组合的偏差。

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