Forecasting Accuracy
The forecast error is the difference between the actual value and the forecast value for the corresponding period.
where E is the forecast error at period t, Y is the actual value at period t, and F is the forecast for period t.
Measures of aggregate error:
| Mean absolute error (MAE) | |
| Mean Absolute Percentage Error (MAPE) | |
| Mean Absolute Deviation (MAD) | |
| Percent Mean Absolute Deviation (PMAD) | |
| Mean squared error (MSE) or Mean squared prediction error (MSPE) | |
| Root Mean squared error (RMSE) | |
| Forecast skill (SS) | |
| Average of Errors (E) |
Business forecasters and practitioners sometimes use different terminology in the industry. They refer to the PMAD as the MAPE, although they compute this as a volume weighted MAPE. For more information see Calculating demand forecast accuracy.
See also
- Calculating demand forecast accuracy
- Consensus forecasts
- Forecast error
- Predictability
- Prediction intervals, similar to confidence intervals
- Reference class forecasting
Read more about this topic: Statistical Forecasting
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