A simple smooth backfitting method for additive models
Statistics Theory
2007-06-13 v1 Statistics Theory
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.
Keywords
Cite
@article{arxiv.math/0702657,
title = {A simple smooth backfitting method for additive models},
author = {Enno Mammen and Byeong U. Park},
journal= {arXiv preprint arXiv:math/0702657},
year = {2007}
}
Comments
Published at http://dx.doi.org/10.1214/009053606000000696 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)