A Fast and Efficient Cross-Validation Method for Smoothing Parameter Choice in Spline Regression
针对非参数回归中的样条平滑方法，提出一种近似交叉验证法，只需线性计算时间，模拟显示统计性质良好，并给出数学依据。
The spline smoothing approach to nonparametric regression is considered, with particular reference to the problem of choosing how much to smooth. Both computational and statistical aspects of the method of cross-validation are discussed. An approximate cross-validation method is proposed that requires a small linear amount of computer time. A simulation study indicates that the method has very good statistical properties. Some mathematical justification and motivation are also provided.