Scaled Errors: The forecast error, E, is on the same scale as the data, as such, these accuracy measures are scale-dependent and cannot be used to make comparisons between series on different scales. | |
Mean absolute error (MAE) or mean absolute deviation (MAD) | |
Mean squared error (MSE) or mean squared prediction error (MSPE) | |
Root mean squared error (RMSE) | |
Average of Errors (E) | |
Percentage Errors: These are more frequently used to compare forecast performance between different data sets because they are scale-independent. However, they have the disadvantage of being extremely large or undefined if Y is close to or equal to zero. | |
Mean absolute percentage error (MAPE) or mean absolute percentage deviation (MAPD) | |
Scaled Errors: Hyndman and Koehler (2006) proposed using scaled errors as an alternative to percentage errors. | |
Mean absolute scaled error (MASE) | m=seasonal period or 1 if non-seasonal |
Other Measures: | |
Forecast skill (SS) |
Look up predict in Wiktionary, the free dictionary. |
Look up forecast in Wiktionary, the free dictionary. |