Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/176049 
Year of Publication: 
2010
Series/Report no.: 
Texto para discussão No. 566
Publisher: 
Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Departamento de Economia, Rio de Janeiro
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.
Subjects: 
fuzzy rule-based models
time series
linearity test
statistical inference
Document Type: 
Working Paper

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