TY - JOUR
T1 - Linearity testing for fuzzy rule-based models
AU - Aznarte, José Luis
AU - Medeiros, Marcelo C.
AU - Benítez, José M.
N1 - Funding Information:
The research included in this work is part of the first author’s PhD dissertation at the Department of Computer Science and Artificial Intelligence of the University of Granada. It has been partially supported by the Ministerio de Ciencia e Innovación of the Spanish Government through Research Grants Ref. TIN2009-14575 and CIT-460000-2009-46.
PY - 2010/7/1
Y1 - 2010/7/1
N2 - 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.
AB - 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.
KW - Fuzzy rule-based models
KW - Linearity test
KW - Statistical inference
KW - Time series
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U2 - 10.1016/j.fss.2010.01.005
DO - 10.1016/j.fss.2010.01.005
M3 - Article
AN - SCOPUS:77950629339
SN - 0165-0114
VL - 161
SP - 1836
EP - 1851
JO - Fuzzy Sets and Systems
JF - Fuzzy Sets and Systems
IS - 13
ER -