Model Initialization
Purpose
Model initialization is the process by which the system determines the necessary model parameters for the chosen forecast model. These parameters are as follows:
Model |
Model parameters |
Constant models |
Basic value = Hist(1) where Hist(i) is the ith historical value Trend value = 0 Seasonal indices = 1 Mean absolute deviation (MAD) = 0 |
Trend models |
Trend value =
Basic value =
Seasonal indices = 1 Mean absolute deviation (MAD) =
|
Seasonal models |
Basic value = Mean of the historical values of the first historical season Trend value = 0 Seasonal index for a period = Historical value for that period divided by the basic value Mean absolute deviation (MAD) = 0 |
Seasonal trend models |
Trend value =
Basic value =
Seasonal index for a period =
where S(i) is the ith seasonal index. Mean absolute deviation (MAD) =
|
The system uses a fixed number of historical values to carry out model initialization. This number depends on the forecast model:
Model |
Fixed number of historical values used for initialization |
Constant |
1 |
Trend |
3 |
Seasonal |
1 season |
Seasonal trend |
3 + 1 season |
Automatic model selection with selection with seasonal test |
2 seasons |
Automatic model selection with seasonal + trend tests |
3 + 2 seasons |
2nd-order exponential smoothing |
3 |