Confidence Bands in Nonparametric Regression
提出了一种新的偏差校正置信带，用于非参数核回归，仅使用回归曲线的核估计及其数据选择的带宽，在大样本下渐近覆盖正确，小样本表现良好。
Abstract New bias-corrected confidence bands are proposed for nonparametric kernal regression. These bands are constructed using only a kernel estimator of the regression curve and its data-selected bandwidth. They are shown to have asymptotically correct coverage properties and to behave well in a small-sample study. One consequence of the large-sample developments is that Bonferroni-type bands for the regression curve at the design points also have conservative asymptotic coverage behavior with no bias correction.