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Table 5

Test result of the different models

ModelMAEWeighted MAERMSEWeighted RMSECRPS
0.0508 0.0537 0.0607 0.0648 0.03776 
0.0465 0.0491 0.0567 0.0602 0.07472 
0.0460 0.0487 0.0556 0.0590 0.03440 
0.0460 0.0486 0.0555 0.0589 0.03440 
0.0462 0.0488 0.0558 0.0590 0.03418 
0.0493 0.0520 0.0596 0.0632 0.07675 
0.0467 0.0490 0.0561 0.0590 0.03451 
0.0477 0.0504 0.0572 0.0608 0.03538 
0.0465 0.0490 0.0567 0.0600 0.06931 
0.1487 0.1497 0.1577 0.1593 0.08074 
Sturm 0.0617 0.0636 0.0719 0.0743 0.06170 
ModelMAEWeighted MAERMSEWeighted RMSECRPS
0.0508 0.0537 0.0607 0.0648 0.03776 
0.0465 0.0491 0.0567 0.0602 0.07472 
0.0460 0.0487 0.0556 0.0590 0.03440 
0.0460 0.0486 0.0555 0.0589 0.03440 
0.0462 0.0488 0.0558 0.0590 0.03418 
0.0493 0.0520 0.0596 0.0632 0.07675 
0.0467 0.0490 0.0561 0.0590 0.03451 
0.0477 0.0504 0.0572 0.0608 0.03538 
0.0465 0.0490 0.0567 0.0600 0.06931 
0.1487 0.1497 0.1577 0.1593 0.08074 
Sturm 0.0617 0.0636 0.0719 0.0743 0.06170 

Framed values indicate the best score for the different evaluation criteria.

MAE: mean absolute error; RMSE: root mean square error; CRPS: continuous ranked probability score.

Both MAE and RMSE scores are also weighed by the number of observations.

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