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Adaptive orthogonal series estimation in additive stochastic regression models

Gao, Jiti, Tong, Howell, & Wolff, Rodney C. (2002) Adaptive orthogonal series estimation in additive stochastic regression models. Statistica Sinica, 12(2), pp. 409-428.

Abstract

In this paper, we consider additive stochastic nonparametric regression models. By approximating the nonparametric components by a class of orthogonal series and using a generalized cross-validation criterion, an adaptive and simultaneous estimation procedure for all the nonparametric components is constructed. We illustrate the adaptive and simultaneous estimation procedure by a number of simulated and real examples.

Impact and interest:

2 citations in Scopus
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2 citations in Web of Science®

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352 since deposited on 16 Jan 2007
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ID Code: 5990
Item Type: Journal Article
Additional URLs:
Keywords: Adaptive estimation, additive model, dependent process, mixing condition, nonlinear time series, nonparametric regression, orthogonal series, strict stationarity, truncation parameter
ISSN: 1017-0405
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > PURE MATHEMATICS (010100)
Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400)
Australian and New Zealand Standard Research Classification > ECONOMICS (140000) > ECONOMETRICS (140300)
Divisions: Current > QUT Faculties and Divisions > QUT Business School
Copyright Owner: Copyright 2002 Institute of Statistical Science, Academia Sinica
Copyright Statement: Reproduced in accordance with the copyright policy of the publisher.
Deposited On: 16 Jan 2007
Last Modified: 05 Jan 2011 23:29

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