Theory for penalised spline regression

Date

2005

Authors

Hall, Peter
Opsomer, J D

Journal Title

Journal ISSN

Volume Title

Publisher

Biometrika Trust

Abstract

Penalised spline regression is a popular new approach to smoothing, but its theoretical properties are not yet well understood. In this paper, mean squared error expressions and consistency results are derived by using a white-noise model representation for the estimator. The effect of the penalty on the bias and variance of the estimator is discussed, both for general splines and for the case of polynomial splines. The penalised spline regression estimator is shown to achieve the optimal nonparametric convergence rate established by Stone (1982).

Description

Keywords

Keywords: Nonparametric regression; White noise model

Citation

Source

Biometrika

Type

Journal article

Book Title

Entity type

Access Statement

License Rights

Restricted until

2037-12-31