Testing For Remaining Autocorrelation Of The Residuals In The Framework Of Fuzzy Rule-Based Time Series Modelling

In time series analysis remaining auto correlation in the errors of a model implies that it is failing to properly capture the structure of time-dependence of the series under study. This can be used as a diagnostic checking tool and as an indicator of the adequacy of the model.Through the study of the errors of the model in the Lagrange Multiplier testing framework, in this paper we derive (and validate using simulated and real world examp les) stop towards statistically sound modelling strategy for fuzzy rule-based models.