Forecast Parameters: Dependent on the Forecast Model
You can/must maintain the following parameters depending on how you carry out model selection and which model you choose. The relationship between parameters and model selection is shown in the following two tables.
Parameters Dependent on Model Selection
Model selection 
Parameters 
Manual model 
forecast model selection 
Automatic 
model selection, model selection procedure model selection 
Parameters Dependent on the Forecast Model
Specified model/ model to be tested 
Possible/required parameters 
Constant model 
parameter optimization 
optimization level 

alpha and delta factors 

Constant model with optimization of the smoothing factors 
 
Trend model 
parameter optimization 
optimization level 

alpha, beta and delta factors 

Moving average model 
initialization periods 
Weighted moving average 
weighting group model 
Extended forecast component used: 

Seasonal model 
parameter optimization 
optimization level 

alpha, beta and delta factors 

Seasonal trend model 
parameter optimization 
optimization level 

alpha, beta, gamma and 

delta factors 

2ndorder exponential smoothing model 
parameter optimization 
alpha and delta factors 

2ndorder exponential smoothing model with smoothing factor optimization 
alpha and delta factors 
Forecast model
You determine via the forecast model which model the system uses as a basis when calculating the forecast values. If you do not know the forecast model, you can have it determined by the system via automatic model selection.
Model selection
This indicator specifies for which model the system is to examine the historical values. You can specify whether the system searches the historical values
Please note that depending on the model test, a minimum number of historical values must be available. This field is significant if you do not know the model and you want the system to determine it automatically. Furthermore, you also have the possibility of preselecting a trend model, but at the same time instruct the system to search for a seasonal pattern and vice versa.
Selection procedure
This indicator specifies how the system is to carry out the model selection. Here, you can choose between two procedures:
Parameter optimization
Via this indicator, you can specify that the system is to optimize the necessary smoothing factors for the appropriate model. The system calculates several parameter combinations and selects the one that displays the lowest MAD. Parameter optimization is carried for the initial forecast as well as for the subsequent forecasts.
Periods per seasonal cycle
You must enter the number of periods that constitute a season here if you have selected a seasonal model or if the system is to carry out a seasonal test.
Optimization level
By determining the optimization level, you are specifying the increment with which the system is to carry out parameter optimization. The lower the increment, the more exact but also the more time consuming the optimization process will be.
Weighting group
You only have to maintain this field if you selected the forecast model, "weighted moving average". This key specifies how many historical values are taken into account for the forecast and how these values are weighted in the forecast calculation.
The following factors are used by the system, depending on the model, for exponential smoothing. Thus, for example, only the alpha and the delta factors are required for the constant model whereas all of the smoothing factors are required for the seasonal trend model.
Alpha factor
The system uses the alpha factor for smoothing the basic value. If you do not specify an alpha factor, the system will automatically use the alpha factor 0.2.
Beta factor
The system uses the beta factor for smoothing the trend value. If you do not specify a beta factor, the system will autimatically use the beta factor 0.1.
Gamma factor
The system uses the gamma factor for smoothing the seasonal index. If you do not specify a gamma factor, the system will automatically use the gamma factor 0.3.
Delta factor
The system uses the delta factor for smoothing the mean absolute deviation and the error total. If you do not specify a delta factor, the system will automatically use the delta factor 0.3.
If you set parameter optimization, the system will overwrite the originally set smoothing factors with those which have been newly calculated by the optimization process.