MRP 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
2nd-order exponential smoothing model	parameter optimization
	alpha and delta factors
2nd-order 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

• for a constant pattern

• for a pattern corresponding to the trend model type

• for a seasonal pattern or

• for both a trend model pattern and a seasonal pattern.

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 pre-selecting 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:

• The first procedure involves the system carrying out a significance test and then selecting the appropriate model.

• The second procedure involves the system determining the mean absolute deviation (MAD) using various parameter combinations for the models to be tested and then selecting the model which displays the lowest MAD. This procedure takes considerably longer than the first procedure.

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.