The Annals of Statistics

A simple smooth backfitting method for additive models

Enno Mammen and Byeong U. Park

Full-text: Open access

Abstract

In this paper a new smooth backfitting estimate is proposed for additive regression models. The estimate has the simple structure of Nadaraya–Watson smooth backfitting but at the same time achieves the oracle property of local linear smooth backfitting. Each component is estimated with the same asymptotic accuracy as if the other components were known.

Article information

Source
Ann. Statist., Volume 34, Number 5 (2006), 2252-2271.

Dates
First available in Project Euclid: 23 January 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1169571796

Digital Object Identifier
doi:10.1214/009053606000000696

Mathematical Reviews number (MathSciNet)
MR2291499

Zentralblatt MATH identifier
1106.62042

Subjects
Primary: 62G07: Density estimation
Secondary: 62G20: Asymptotic properties

Keywords
Backfitting nonparametric regression local linear smoothing

Citation

Mammen, Enno; U. Park, Byeong. A simple smooth backfitting method for additive models. Ann. Statist. 34 (2006), no. 5, 2252--2271. doi:10.1214/009053606000000696. https://projecteuclid.org/euclid.aos/1169571796


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