A simple smooth backfitting method for additive models
The Annals of Statistics · 2006 · Volume 34 · Issue 5
DOI: 10.1214/009053606000000696
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
62G07, 62G20, backfitting, local linear smoothing, Nonparametric regression
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