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Tukey's M-estimator of the Poisson parameter with a special focus on small means

机译:Tukey的Poisson参数的M估计量,特别关注小均值

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We treat robust M-estimators for independent and identically distributed Poisson data. We introduce modified Tukey M-estimators with bias correction and compare them to M-estimators based on the Huber function as well as to weighted likelihood and other estimators by simulation in case of clean data and data with outliers. In particular, we investigate the problem of combining robustness and high efficiencies at small Poisson means caused by the strong asymmetry of such Poisson distributions and propose a further estimator based on adaptive trimming. The advantages of the constructed estimators are illustrated by an application to smoothing count data with a time varying mean and level shifts.
机译:对于独立且分布均匀的泊松数据,我们使用健壮的M估计量。我们介绍了经过修正的具有偏差校正功能的Tukey M估计量,并将它们与基于Huber函数的M估计量以及加权似然法和其他估计量进行了比较(通过模拟得出的情况),以得到干净的数据和带有异常值的数据。特别是,我们研究了由此类Poisson分布的强不对称性导致的在小Poisson手段下将鲁棒性和高效性相结合的问题,并提出了一种基于自适应修整的进一步估计器。通过使用随时间变化的平均值和水平偏移对计数数据进行平滑处理的应用,可以说明构造的估算器的优势。

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