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Interval estimation of binomial proportions based on weighted Polya posterior

机译:基于加权Polya后验的二项式比例的区间估计

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摘要

Recently the interval estimation of binomial proportions is revisited in various literatures. This is mainly due to the erratic behavior of the coverage probability of the well-known Wald confidence interval. Various alternatives have been proposed. Among them, Agresti–Coull confidence interval has been recommended by Brown et al. [2001. Interval estimation for a binomial proportion. Statist. Sci. 16, 101–133] with other confidence intervals such as the Wilson interval and the equal tailed interval resulting from the natural noninformative Jefferys prior for a binomial proportion. However, it seems that Agresti–Coull interval is little bit wider than necessary when sample size is small, say n40. In this note, an interval estimator is developed using weighted Polya posterior. It is shown that the confidence interval based on the weighted Polya posterior is essentially the Agresti–Coull interval with some improved features.
机译:最近,在各种文献中都重新考虑了二项式比例的区间估计。这主要是由于众所周知的Wald置信区间的覆盖概率的行为不稳定。已经提出了各种替代方案。其中,Brown等人推荐了Agresti-Coull置信区间。 [2001。二项式比例的区间估计。统计员。科学[16,101–133]以及其他置信区间,例如威尔逊区间和自然无信息的杰弗里斯在二项式比例之前产生的等尾区间。但是,当样本量较小(例如n40)时,似乎Agresti-Coull间隔稍宽于必要间隔。在本说明中,使用加权的Polya后验开发了区间估计器。结果表明,基于加权Polya后验的置信区间实质上是具有一些改进特征的Agresti-Coull区间。

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