Why Bandwidth Selectors Tend to Choose Smaller Bandwidths, and a Remedy
解释了非参数回归中数据驱动带宽选择器为何常偏向欠平滑，并基于经典选择器提出一种简单修改，模拟表明新选择器更一致。
This note is concerned with the problem of automatic data-driven bandwidth selectors for nonparametric regression. Though some selectors were shown to be consistent and asymptotically unbiased by Rice (1984) and Hãrdle, Hall & Marron (1988), it is often observed in simulation studies that most selectors are biased toward undersmoothing. An explanation for this is given. The source of the large sample variation in the bandwidth estimates is also pointed out. This leads to the consideration of a new procedure which is a simple modification of a classical selector. A simulation study suggests that the proposed selector is much more consistent than the classical one.