On model selection criteria as a starting point for sequential detection of non-linearity
نویسندگان
چکیده
Many non-linearity tests have been developed to apply on specific time series, but non of the tests has proved uniformly most powerful; depending on the situation another test may perform better in distinguishing between truly linear and non-linear series. In this context, Peña and Rodriguez circumvent the philosophical question as to the nature of non-linearity in order to find and develop a new method of detecting the lack of linearity. They propose an original checking procedure, not a test, based on the most common model selection criteria, the BIC, AIC or AICc. A large Monte Carlo simulation study and a very illustrative real data example show the effectiveness of this new tool, in comparison with a range of well know statistics.
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