12.2 Performance Measurements
12.2.1 Error terms
- Mean error (ME):
ME=1n∑(Yt−ˆYt)$
- Mean Absolute Deviation (error):
MAD(i.e. MAE) = 1n⋅∑|Yt−ˆYt|
- Mean Percentage Error (MPE):
MPE = 1n ∑(Yt−ˆYt)Yt
- Mean Absolute Percentage Error (MAPE):
MAPE = 1n ∑|(Yt−ˆYt)||Yt|
- Mean-Squared Error (MSE):
MSE=1n∑(Yt−ˆYt)2
- Root Mean-Squared Error:
RMSE=√MSE
12.2.2 Multicollinearity
VIF
VIFj=11−R2j
Where j=1,...,k
Thus, we see that Rsquare is obtained from regression each IDV against the remaining variables. We can then have the following outputs:
- VIF = 1, no milticollinearity
- VIF > 10, indicates multicollinearity
If one gets an indication of multicollinearity, then one should drop one of the correlated variables.