Forecasting with Time Series Models

Having selected a model and fitted its parameters to a given times series, the model can then be used to estimate new data of the time series. If such data are estimated for a time period following the final data value XT of the given time series, we speak of a prediction or forecast. The estimation of data lying between given data points is called interpolation. The question now arises as to how a model such as those given in Equations 30.6 or 30.13 could be used to obtain an “optimal” estimate.