论文标题
天真的惩罚衍生物的样条估计器达到了最佳的收敛速率
Naive Penalized Spline Estimators of Derivatives Achieve Optimal Rates of Convergence
论文作者
论文摘要
本文研究了衍生物的渐近样条估计的渐近行为。特别是，我们表明，简单地区分平均回归函数的惩罚样条估计器本身以估计相应的衍生物达到最佳的L2收敛速率。
This paper studies the asymptotic behavior of penalized spline estimates of derivatives. In particular, we show that simply differentiating the penalized spline estimator of the mean regression function itself to estimate the corresponding derivative achieves the optimal L2 rate of convergence.
