Model initialization is the process of determining the necessary model parameters¾such as the basic value, the trend value, and the seasonal indices ¾for the selected forecast model. Initialization takes place each time a planning time series is forecasted.

The following table shows you which model parameters are necessary for each forecast model.

As a general rule, the forecast model is initialized automatically. In order to do this, the system requires a certain number of historical values. This number depends on the forecast model, as shown in the following table.

The system calculates the basic value on the basis of the average and the trend using the results of the regression analysis. The seasonal indices are given by the actual historical value divided by the basic value adjusted for the trend value.

These calculation methods are used for the constant, trend, seasonal, and seasonal trend models, depending on which parameters are to be determined.

A regression analysis is carried out for the second-order exponential smoothing model.

For the moving average and weighted moving average models, the system calculates an average value.