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Biometrika 1997 84(2):469-473; doi:10.1093/biomet/84.2.469
© 1997 by Biometrika Trust
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MISCELLANEA

Miscellanea Efficient estimation of additive nonparametric regression models

OLIVER B. LINTON

Cowles Foundation for Research in Economics, Yale University New Haven, Connecticut 06520, U.S.A. e-mail: linton{at}econ.yale.edu

We define a new procedure for estimating additive nonparametric regression models. We use the integration method of Linton & Nielsen (1995) to provide starting values that are then used in a one-step backfitting procedure. We show that our new method is efficient in a certain sense and dominates the straight integration method according to mean squared error.

Key Words: Additive regression models • Backfitting • Dimensionality reduction • Kernel estimation • Nonparametric regression


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