A Radial Basis Function Artificial Neural Network Test For Neglected Nonlinearity  

Oleh:

Blake, Andrew P. ; Kapetanios, George

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: The Econometrics Journal vol. 6 no. 2 (Dec. 2003), page 357–373.
Topik: Nonlinearity tests; Artificial neural networks; Radial basis functions; Information criteria
Fulltext: 357.pdf (82.82KB)

Isi artikel

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 Ter¨asvirta et al. (1993).

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