Extension of the subset interactive AR model using non-monotonic fuzzy measures

The authors propose an extended subset interactive autoregressive (AR) model using non-monotonic fuzzy measures and the Choquet integral. Genetic algorithms (GAs) and the statistical model selection criterion (i.e., Akaike´s information criterion, AIC) are used for the identification of the proposed model. The fitting and forecasting performances of the proposed model are analyzed by applying it to well-known time series data, the sunspot series. The results show that the proposed model is useful for time series analysis with nonlinear features.