Department of Automatic Control and Systems Engineering
Abstract
A new direct approach of computing multi-step ahead predictions for nonlinear time series is introduced. The covariance of the parameter estimates associated with, and the mean squared k-step ahead prediction errors of the new direct approach are smaller than those obtained using the conventional direct approach. Numerical examples are included to illustrate the application of the new direct approach
