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Efficient estimation of generalized additive nonparametric regression models

By Oliver Linton

Abstract

We define new procedures for estimating generalized additive nonparametric regression models that are more efficient than the Linton and Härdle (1996, Biometrika 83, 529–540) integration-based method and achieve certain oracle bounds. We consider criterion functions based on the Linear exponential family, which includes many important special cases. We also consider the extension to multiple parameter models like the gamma distribution and to models for conditional heteroskedasticity

Topics: HB Economic Theory
Publisher: Cambridge University Press
Year: 2000
DOI identifier: 10.1017/S0266466600164023
OAI identifier: oai:eprints.lse.ac.uk:314
Provided by: LSE Research Online
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    Citations

    1. (1985). Estimating optimal transformations for multiple regression and correlation, ~with discussion!+

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