# Acceptable limit for MASE

What are good sign of fit from result of forecast::accuracy.

How to interpret

                  ME          RMSE      MAE       MPE     MAPE     MASE      ACF1

Training set -2.055155e-16 5.764161 4.322594 -8.302648 17.98444 6.244566 0.8651557

Test set      1.038893e+00 5.857035 4.353372 -4.400336 16.60394 6.289029        NA

• Pass on this, but a bad sign is any report implying that we can and should be thinking about 7 significant figures. – Nick Cox Oct 29 '15 at 17:06
• I guess most statistically minded people know two or three of these immediately from the abbreviations. Perhaps only forecasting experts will know all of them at first sight. I suppose that doesn't matter because it is the latter who should be able to produce good answers. But FWIW I flag the need to explain these to any but a highly trained readership. – Nick Cox Oct 29 '15 at 17:10
• @NickCox: re your first comment, I agree that seven sig figs are too many, but believe me - the author of the forecast package knows what he's doing. – Stephan Kolassa Oct 29 '15 at 20:09
• MASE is one of the most extremely confusing error metric, very difficult to explain to a non technical audience, use mean absolute error if you are comparing similar measure of units. MEan absolute percentage error (MAPE) or symmetric mean absolute percentage error (sMAPE) if you have different measure of units. – forecaster Oct 30 '15 at 2:04
• I see no justification of using MASE, unless you have zeros in your forecast which in real world forecasting is almost non existent except intermittent demand forecasting. – forecaster Oct 30 '15 at 2:12