학술논문

Naive Penalized Spline Estimators of Derivatives Achieve Optimal Rates of Convergence
Document Type
Working Paper
Source
Subject
Mathematics - Statistics Theory
Computer Science - Machine Learning
Language
Abstract
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.