Efficient estimation of generalized additive nonparametric regression models

Oliver Linton

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

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.

JEL-codes: J1 (search for similar items in EconPapers)
Date: 2000-08
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Citations: View citations in EconPapers (29)

Published in Econometric Theory, August, 2000, 16(4), pp. 502-523. ISSN: 0266-4666

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Related works:
Journal Article: EFFICIENT ESTIMATION OF GENERALIZED ADDITIVE NONPARAMETRIC REGRESSION MODELS (2000)
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:314

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