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A radial basis function artificial neural network test for neglected nonlinearity

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Author Info
Andrew P. Blake
George Kapetanios

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Abstract

We propose a test for neglected nonlinearity that uses an alternative artificial neural network (ANN) specification to the one commonly used in the literature. We use radial basis functions for the "hidden layer" with basis function centres and radii chosen from the sample data set and selected on the basis of an information criterion. The procedure is straightforward to implement and outperforms, in many cases, the ANN test proposed by Lee et al. (1993) and the analytic variation devised by Terasvirta et al. (1993) Copyright Royal Economic Society, 2003

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Article provided by Royal Economic Society in its journal The Econometrics Journal.

Volume (Year): 6 (2003)
Issue (Month): 2 (December)
Pages: 357-373
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Handle: RePEc:ect:emjrnl:v:6:y:2003:i:2:p:357-373

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