Model selection in nonparametric regression

Marten Wegkamp

doi:10.1214/aos/1046294464

Password Forgot your password?

Show

Remember Email on this computer

Remember Password

Please wait...

No Project Euclid account? Create an account
or Sign in with your institutional credentials

We can help you reset your password using the email address linked to your Project Euclid account.

Registered users receive a variety of benefits including the ability to customize email alerts, create favorite journals list, and save searches. Please note that a Project Euclid web account does not automatically grant access to full-text content. An institutional or society member subscription is required to view non-Open Access content. Contact customer_support@projecteuclid.org with any questions.
View Project Euclid Privacy Policy

All Fields are Required

* First Name

* Last/Family Name

* Email

* Password

Password Requirements: Minimum 8 characters, must include as least one uppercase, one lowercase letter, and one number or permitted symbol Valid Symbols for password:
~ Tilde
! Exclamation Mark
@ At sign
$ Dollar sign
^ Caret
( Opening Parenthesis
) Closing Parenthesis
_ Underscore
. Period

* Confirm Password

Please wait...

Web Account created successfully

Browse
Resources
About

Advanced Search

Home > Journals > Ann. Statist. > Volume 31 > Issue 1 > Article

Februrary 2003 Model selection in nonparametric regression

Marten Wegkamp

Ann. Statist. 31(1): 252-273 (Februrary 2003). DOI: 10.1214/aos/1046294464

ABOUT
FIRST PAGE
CITED BY
REFERENCES
DOWNLOAD PAPER SAVE TO MY LIBRARY

PERSONAL SIGN IN
Full access may be available with your subscription

Password Forgot your password?

Show

Remember Email on this computer

Remember Password

No Project Euclid account? Create an account
or Sign in with your institutional credentials

PURCHASE SINGLE ARTICLE

This article is only available to subscribers. It is not available for individual sale.

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Password Forgot your password?

Show

Remember Email on this computer

Remember Password

No Project Euclid account? Create an account

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Abstract

Model selection using a penalized data-splitting device is studied in the context of nonparametric regression. Finite sample bounds under mild conditions are obtained. The resulting estimates are adaptive for large classes of functions.

Citation

Download Citation

Marten Wegkamp. "Model selection in nonparametric regression." Ann. Statist. 31 (1) 252 - 273, Februrary 2003. https://doi.org/10.1214/aos/1046294464

Information

Published: Februrary 2003

First available in Project Euclid: 26 February 2003

zbMATH: 1019.62037

MathSciNet: MR1962506

Digital Object Identifier: 10.1214/aos/1046294464

Subjects:

Primary: 60F05 , 60F17

Secondary: 60G15 , 62E20

Keywords: adaptive estimation , ‎classification‎ , data-splitting , Least squares estimation , Model selection , penalized least squares , VC-major classes