# Forecasting Performance

Forecasting process improvement begins with process measurement. There are dozens of available forecasting performance metrics. Some, like mean absolute percent error (MAPE), represent error as a percentage. Others, like mean absolute error (MAE), are scale dependent. Relative-error metrics (such as MASE) compare performance versus a benchmark (typically a naïve model). Each metric has its place—a situation where it is suitable to use and informative.

- SSE - Sum of Squared Errors
- MSE - Mean Squared Error
- GMSE – Geometric Mean Squared Error
- SAE - Sum of Absolute Errors
- MAE - Mean Absolute Error
- RMSE - Root Mean Squared Error
- RMSD - Root Mean Squared Deviations
- GRMSE – Geometric Root Mean Square Error
- MAPE - Mean Absolute Percentage Error
- MdAPE - Median Absolute Percentage Error
- MAAPE - Mean Arctangent Absolute Percentage Error
- MRAE – Mean Relative Absolute Error
- MdRAE - Median Relative Absolute Error
- GMRAE – Geometric Mean Relative Absolute Error
- MASE - Mean Absolute Scaled Error
- PB - Percentage Better
- MDA - Mean Directional Accuracy