Open Access
February 1997 Local asymptotics for quantile smoothing splines
Stephen Portnoy
Ann. Statist. 25(1): 414-434 (February 1997). DOI: 10.1214/aos/1034276636

Abstract

Quantile smoothing splines were introduced by Koenker, Ng and Portnoy as natural and appealing estimates of conditional quantiles of response variables. The natural setting for the problem considers minimization of a weighted combination of a "fit" penalty and a "roughness" penalty over the space of functions whose derivatives have bounded variation. Although this space is not traditional, Shen has shown recently that the quantile smoothing splines do indeed converge at the usual optimal rate $n^{-2/5)$ in various norms. Here, local asymptotic results are obtained by establishing Bahadur representations for local parameters of the splines. These are used to obtain local rates of convergence, to establish uniform convergence rates, to provide local distribution theory for quantile B-splines and to expand the "fit" measure in order to analyze an information criterion for determining the smoothing parameter. Examples of using derivatives of the smoothing splines for estimating jump functions are also presented.

Citation

Download Citation

Stephen Portnoy. "Local asymptotics for quantile smoothing splines." Ann. Statist. 25 (1) 414 - 434, February 1997. https://doi.org/10.1214/aos/1034276636

Information

Published: February 1997
First available in Project Euclid: 10 October 2002

zbMATH: 0898.62044
MathSciNet: MR1429932
Digital Object Identifier: 10.1214/aos/1034276636

Subjects:
Primary: 62E20 , 62G05

Keywords: conditional quantiles , Nonparametric regression , rates of convergence

Rights: Copyright © 1997 Institute of Mathematical Statistics

Vol.25 • No. 1 • February 1997
Back to Top