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A radial basis function artificial neural network test for neglected nonlinearity

Andrew Peter Blake () and George Kapetanios

Econometrics Journal, 2003, vol. 6, issue 2, pages 357-373

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

Date: 2003

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Working Paper: A Radial Basis Function Artificial Neural Network Test for Neglected Nonlinearity (1999) Downloads
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Econometrics Journal is edited by Richard J. Smith, Oliver Linton, Pierre Perron, Jean-Marc Robin, Alessio Sancetta and Marius Ooms

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