Efficient estimation of generalized additive nonparametric regression models

Linton, Oliver (2000) Efficient estimation of generalized additive nonparametric regression models. Econometric Theory, 16 (4). pp. 502-523. ISSN 0266-4666

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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.

Item Type:	Article
Official URL:	http://uk.cambridge.org/journals/ect/
Additional Information:	Published [2000] © Cambridge University Press. LSE has developed LSE Research Online so that users may access research output of the School. Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Users may download and/or print one copy of any article(s) in LSE Research Online to facilitate their private study or for non-commercial research. You may not engage in further distribution of the material or use it for any profit-making activities or any commercial gain. You may freely distribute the URL (http://eprints.lse.ac.uk) of the LSE Research Online website.
Divisions:	Financial Markets Group STICERD Economics
Subjects:	H Social Sciences > HB Economic Theory
Date Deposited:	15 Feb 2008
Last Modified:	21 Oct 2024 00:57
URI:	http://eprints.lse.ac.uk/id/eprint/314

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