High-derivative parametric enhancements of nonparametric curve estimators

Loading...
Thumbnail Image

Date

Authors

Hall, Peter
Cheng, Ming-Yen
Turlach, B

Journal Title

Journal ISSN

Volume Title

Publisher

Biometrika Trust

Abstract

We suggest a method for using parametric information to modify a nonparametric estimator at the level of relatively high-order derivatives. The technique represents an alternative to methods that first fit a parametric model and then adjust it. In particular, relative to a 'nonparametric estimator with a parametric start', our estimator is not biased by the differences between parametric and nonparametric fits to low-order derivatives, since we effectively remove all the parametric information about low-order derivatives and replace it by nonparametric information. Thus, we employ parametric information only when the nonparametric information is unreliable, and do not use it elsewhere. The method has application to both nonparametric density estimation and nonparametric regression.

Description

Citation

Source

Biometrika

Book Title

Entity type

Access Statement

License Rights

DOI

Restricted until

2037-12-31