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Linearity Testing Against a Fuzzy Rule-based Model

Author

Listed:
  • José Luis Aznarte

    (Department of Computer Science and Artificial Intelligence,CITIC-UGR, University of Granada, (Spain))

  • Marcelo Cunha Medeiros

    (Department of Economics PUC-Rio)

  • José Manuel Benítez Sánchez

    (Department of Computer Science and Artificial Intelligence,CITIC-UGR, University of Granada, (Spain))

Abstract

In this paper, we introduce a linearity test for fuzzy rule-based models in the framework of time series modeling. To do so, we explore a family of statistical models, the regime switching autoregressive models, and the relations that link them to the fuzzy rule-based models. From these relations, we derive a Lagrange Multiplier linearity test and some properties of the maximum likelihood estimator needed for it. Finally, an empirical study of the goodness of the test is presented.

Suggested Citation

  • José Luis Aznarte & Marcelo Cunha Medeiros & José Manuel Benítez Sánchez, 2010. "Linearity Testing Against a Fuzzy Rule-based Model," Textos para discussão 566, Department of Economics PUC-Rio (Brazil).
    • Handle: RePEc:rio:texdis:566
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    References listed on IDEAS

    as
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    5. Mayte Suarez -Farinas & Carlos E. Pedreira & Marcelo C. Medeiros, 2004. "Local Global Neural Networks: A New Approach for Nonlinear Time Series Modeling," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1092-1107, December.
    6. Medeiros, Marcelo & Veiga, Alvaro, 2000. "A Flexible Coefficient Smooth Transition Time Series Model," SSE/EFI Working Paper Series in Economics and Finance 360, Stockholm School of Economics, revised 29 Apr 2004.
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    Keywords

    fuzzy rule-based models; time series; linearity test; statistical inference;
    All these keywords.

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