Multiplicative bias correction for asymmetric kernel density estimators revisited
Multiplicative bias correction for asymmetric kernel density estimators revisited
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DOI：
10.1016/j.csda.2019.06.010
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Gaku Igarashi;Yoshihide Kakizawa
中科院分区：
文献类型：
--
作者：
Gaku Igarashi;Yoshihide Kakizawa
当数据为非负或有界数据时，研究了非对称核密度估计的乘性偏差校正技术。将最近开发的非对称KDE分为两种类型是至关重要的。乘法偏差校正适用于非两个政权类型示出，以牺牲一个恒定的因素通货膨胀的方差，以有效地减少偏差的顺序。然而，据透露，在共同与其他偏置校正，乘法偏置校正应用到两个政权类型失败，在减少边界附近的偏差，除非密度估计满足肩条件。
Multiplicative bias correction technique is revisited for asymmetric kernel density estimators (KDEs) when the data is nonnegative or bounded. It is crucial to classify the recently developed asymmetric KDEs into two types. The multiplicative bias correction applied to the non two-regime type is shown to effectively reduce the order of the bias, at the expense of a constant-factor inflation of the variance. However, it is revealed that, in common with other bias corrections, the multiplicative bias correction applied to the two-regime type fails in reducing the bias near the boundary, unless the density to be estimated satisfies the shoulder condition.