A Comparison of Variance Estimators in Nonparametric Regression
比较了两种基于平滑样条残差二次型的误差方差估计量，发现常用估计量在平滑参数较小时会严重低估误差方差，而另一种计算更复杂的估计量则没有这个问题。
SUMMARY We compare two estimators of error variance, both based on quadratic forms in the residuals about smoothing spline fits to data. The estimators are compared over the whole range of values of the smoothing parameter as well as for data-based choices of the smoothing parameter. We show that the commonly used estimator of variance has the serious drawback of underestimating the error variance for small choices of the smoothing parameter. This drawback is not shared by a simple, but more computationally intensive, alternative.