A bootstrap method for narmax model order selection

摘要

NARMAX (Nonlinear AutoRegressive, moving Average eXogenous) models describe nonlinear systems in terms of linear-in-the-parameters difference equations which represent the current output with present and past inputs and past outputs. Identification of NARMAX models requires determining both the model order and parameter values. Good parameter estimation methods exist if the model order is known, however, model order selection remains a problem. We propose a bootstrap-based model order selection algorithm for determining the order of NARMAX systems. The performance of this bootstrap model order selection technique was evaluated by applying it to the slow phase component of the vestibulo-ocular reflex system (Kukreja et al. 1999). Copyright direct C 2000 IFAC