A fuzzy reasoning based approach for ARMA order selection

A fuzzy reasoning based approach for ARMA order selection is discussed in this paper. The proposed method attempts to select the optimal ARMA order of a time-varying ARMA model. This method improves model validity-criterion based order selection, such as the AIC (Akaike's Information Criterion) and the MDL (Minimum Description Length), etc with applying both of a fuzzy reasoning method and a fuzzy c-means clustering method. These fuzzy methods are incorporated in the proposed method as follows: (1) Suppose the ARMA order of the reference time-varying model changes. The suitable ARMA order is selected by utilizing a recursive fuzzy reasoning method. (2) By using a fuzzy c-means clustering method, we detect the time at which the ARMA order of the reference model changes, and the clustering values are used for adaptive setting the forgetting factor in the recursive fuzzy reasoning method. The experimental results show that the proposed method effectively selects the ARMA orders of a time-varying ARMA model.