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Efficient Estimation Of Generalized Additive Nonparametric Regression Models

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Author Info
Linton, Oliver B.

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Abstract

We define new procedures for estimating generalized additive nonparametric regression models that are more efficient than the Linton and H rdle (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.

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File URL: http://journals.cambridge.org/abstract_S0266466600164023
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Publisher Info
Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 16 (2000)
Issue (Month): 04 (August)
Pages: 502-523
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Handle: RePEc:cup:etheor:v:16:y:2000:i:04:p:502-523_16

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  1. Gao, Jiti & King, Maxwell, 2003. "Estimation and model specification testing in nonparametric and semiparametric econometric models," MPRA Paper 11989, University Library of Munich, Germany, revised Feb 2006. [Downloadable!]
  2. Toshio Honda, 2005. "Estimation in additive cox models by marginal integration," Annals of the Institute of Statistical Mathematics, Springer, vol. 57(3), pages 403-423, September. [Downloadable!] (restricted)
  3. Ilze Kalnina & Oliver Linton, 2007. "Inference about Realized Volatility using Infill Subsampling," STICERD - Econometrics Paper Series /2007/523, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE. [Downloadable!]
  4. O. Linton & E. Mammen & J. Nielsen & C. Tanggaard, . "Estimating Yield Curves by Kernel Smoothing Methods," Sonderforschungsbereich 373 1999-54, Humboldt Universitaet Berlin.
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