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Confidence intervals for data containing many zeros and ones based on empirical likelihood-type methods
Journal of Statistical Computation and Simulation ( IF 1.2 ) Pub Date : 2020-08-07
Patrick Stewart, Wei Ning

In this paper, several existing data-driven nonparametric methods including empirical likelihood, adjusted empirical likelihood and transformed empirical likelihood are considered to construct confidence intervals for the mean of a population containing many zeros and ones. Meanwhile, we propose a transformed adjusted empirical likelihood which combines the merits of adjusted and transformed empirical likelihoods. All five methods are compared to normal approximation in terms of coverage probabilities under various scenarios through simulations. All methods are applied to three datasets to illustrate the procedure of obtaining confidence intervals.



中文翻译:

基于经验似然类型方法的包含多个零和一的数据的置信区间

在本文中,考虑了几种现有的由数据驱动的非参数方法,包括经验似然,调整后的经验似然和变换的经验似然,以构造包含多个零和一的总体均值的置信区间。同时,我们提出了一种转换后的调整后经验似然率,该方法结合了调整后和转换后的经验似然率的优点。通过模拟,将这五种方法在各种情况下的覆盖概率方面与正态近似进行了比较。所有方法都应用于三个数据集,以说明获取置信区间的过程。

更新日期:2020-08-08
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