Standard forecasting optimizes the forecasting parameters to minimize the error measure between the fit values and the historical data for the same period. For example, consider Table 5 showing historical data and calculated fit values for periods 1 through 7.
Table 5. Example of Historical Data and Fit with Standard Forecasting
| Period | Historical Data Value | Fit Value |
|---|---|---|
| 1 | 472 | 488 |
| 2 | 599 | 609 |
| 3 | 714 | 702 |
| 4 | 892 | 888 |
| 5 | 874 | 890 |
| 6 | 896 | 909 |
| 7 | 890 | 870 |
Predictor calculates the RMSE using the differences between the historical data and the fit data from the same periods. For example:
(472-488)2 + (599-609)2 + (714-702)2 + (892-888)2 + ...
For standard forecasting, Predictor optimizes the forecasting parameters so that the RMSE calculated in this way is minimized.