A Radial Basis Function Artificial Neural Network Test for Neglected Nonlinearity
We propose a test for neglected nonlinearity that uses an artificial neural network. We use radial basis functions for the `hidden layer' with basis function centers and radii chosen from the sample data set and selected on the basis of information criteria. The procedure is straightforward to implement and out-performs the random network test proposed by Lee, White, and Granger (1993).
Year of publication: |
1999-09
|
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Authors: | Blake, Andrew P ; Kapetanios, George |
Institutions: | National Institute of Economic and Social Research |
Saved in:
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