Empirical Smoothing Parameter Selection in Adaptive Estimation
自适应估计中的经验平滑参数选择
We provide a solution to the smoothing parameter selection problem involved in the construction of adaptive estimates for the symmetric location model and the general linear model. Linear $B$-splines are used to give a simple form of the estimate of the score function of the underlying density. New empirical methods are proposed to locate the knots optimally and to select the number of knots. We also give asymptotic bounds for the empirical selection method and show that an…