Linearity Testing Against a Fuzzy Rule-based Model
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.
|Date of creation:||Mar 2010|
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- Mayte Suarez Farinãs & Carlos Eduardo Pedreira & Marcelo C. Medeiros, 2003.
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470, Department of Economics PUC-Rio (Brazil).
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- Marcelo C. Medeiros & Timo Terasvirta & Gianluigi Rech, 2002.
"Building Neural Network Models for Time Series: A Statistical Approach,"
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461, Department of Economics PUC-Rio (Brazil).
- Timo Teräsvirta & Marcelo C. Medeiros & Gianluigi Rech, 2006. "Building neural network models for time series: a statistical approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 49-75.
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