Table 14 The evaluation measures of different forecasting models in the death cases.
From: A new grey quadratic polynomial model and its application in the COVID-19 in China
GM(1,1) | DGM(1,1) | NGM(1,1,k,c) | GVM(1,1) | PR(2) | GMQP(1,1) | |
|---|---|---|---|---|---|---|
MAEsim | 31.6097 | 33.7059 | 18.1322 | 120.6217 | 1.9217 | 1.5865 |
MAEfit | 239.0131 | 250.7807 | 16.1704 | 297.7345 | 8.4071 | 3.5972 |
MAEall | 70.4979 | 74.4075 | 17.7643 | 153.8304 | 3.1377 | 1.9635 |
MSEsim | 1518.4319 | 1737.0336 | 427.6899 | 21,254.5680 | 5.4033 | 3.2758 |
MSEfit | 62,853.2325 | 68,996.8802 | 373.3784 | 88,872.0233 | 75.9216 | 23.8122 |
MSEall | 13,018.7071 | 14,348.2548 | 417.5065 | 33,932.8408 | 18.6255 | 7.1264 |
MAPEsim | 38.7836 | 39.8725 | 17.9543 | 76.4685 | 2.0505 | 1.6496 |
MAPEfit | 41.5099 | 43.5770 | 3.1013 | 53.1982 | 1.4702 | 0.5921 |
MAPEall | 39.2948 | 40.5671 | 15.1693 | 72.1053 | 1.9417 | 1.4513 |
RMSPEsim | 58.6176 | 59.3060 | 25.9388 | 76.7641 | 2.9375 | 2.0616 |
RMSPEfit | 42.4628 | 44.5301 | 3.7858 | 53.2813 | 1.5009 | 0.7745 |
RMSPEEall | 55.9451 | 56.8289 | 23.4383 | 72.9392 | 2.7265 | 1.8883 |
IAsim | 0.9819 | 0.9794 | 0.9947 | 0.7925 | 0.9999 | 1.0000 |
IAfit | 0.9271 | 0.9220 | 0.9992 | 0.4252 | 0.9998 | 0.9999 |
IAall | 0.9433 | 0.9388 | 0.9972 | 0.6976 | 0.9999 | 1.0000 |
Rsim | 0.9948 | 0.9947 | 0.9996 | 0.9729 | 0.9998 | 0.9999 |
Rfit | 0.9982 | 0.9982 | 0.9992 | 0.9999 | 0.9998 | 0.9997 |
Rall | 0.9870 | 0.9868 | 0.9986 | 0.9756 | 0.9999 | 0.9999 |
