Identification of Multiple‐input Transfer‐function Noise Models: A Regression Approach — Part II: Results and Conclusions

Evaluates an identification strategy, based on ridge regression, for multiple‐input models. The models are essentially the same as those of Edlund, but a far greater number of replications, 1,000, is used in each of the 21 cases tested. Furthermore, users actually identified and estimated ARIMA models of the residuals in the identification procedure of impulse response weights, unlike Edlund, who used only theoretical noise models in filtering the input and output series. A short discussion of the underlying theory was presented in Part I, Kybernetes, Vol. 22 No. 4, 1993, pp. 47–53. In Part II the procedures and results of the empirical testing are published together with some concluding remarks.