A Radial Basis Function Artificial Neural Network Test for Neglected Nonlinearity

Andrew Blake

No 153, National Institute of Economic and Social Research (NIESR) Discussion Papers from National Institute of Economic and Social Research

Abstract: 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).

Date: 1999-09
References: Add references at CitEc
Citations: View citations in EconPapers (4)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: A radial basis function artificial neural network test for neglected nonlinearity (2003)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nsr:niesrd:153

Access Statistics for this paper

More papers in National Institute of Economic and Social Research (NIESR) Discussion Papers from National Institute of Economic and Social Research 2 Dean Trench Street Smith Square London SW1P 3HE. Contact information at EDIRC.
Bibliographic data for series maintained by Library & Information Manager ().