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An improved mean estimator for judgment post-stratification

机译:用于判断分层后的改进的均值估计器

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摘要

We prove that the standard nonparametric mean estimator for judgment post-stratification is inadmissible under squared error loss within a certain class of linear estimators. We derive alternate estimators that are admissible in this class, and we show that one of them is always better than the standard estimator. The reduction in mean squared error from using this alternate estimator can be as large as 10% for small set sizes and small sample sizes.
机译:我们证明在一类线性估计器中,在平方误差损失下,用于判断分层后的标准非参数均值估计器是不可接受的。我们推导了此类中可以接受的替代估计量,我们证明其中之一总是比标准估计量更好。对于较小的样本集和较小的样本量,使用此替代估计量可以减少10%的均方误差。

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