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Effectiveness of neural networks to regression with structural changes

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  • Miyoko Asano
  • Hiroe Tsubaki
  • Tadashi Yoshizawa

Abstract

This paper reports simple numerical experiments of the application of multi‐layered and feed‐forward neural networks to regression with change points to clarify one of the effectiveness of the neural network model compared with non‐parametric regression methods based on scatter plot smoothing. We also show an illustrative example, which successfully draws too rapid growth of GDP in Japan at the bubble economy around 1990 by interpreting decomposition of regression function suggested by the optimal neural networks fitting. Copyright © 2002 John Wiley & Sons, Ltd.

Suggested Citation

  • Miyoko Asano & Hiroe Tsubaki & Tadashi Yoshizawa, 2002. "Effectiveness of neural networks to regression with structural changes," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 18(3), pages 189-195, July.
    • Handle: RePEc:wly:apsmbi:v:18:y:2002:i:3:p:189-195
    DOI: 10.1002/asmb.471
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