Table 3 Results of Statistical analysis for selecting the most efficient model between ULFR and Holt’s.
From: Determining an effective short term COVID-19 prediction model in ASEAN countries
Thailand | Philippines | Singapore | Indonesia | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Day 1 | Day 3 | Day 7 | Day 1 | Day 3 | Day 7 | Day 1 | Day 3 | Day 7 | Day 1 | Day 3 | Day 7 | |
R-squared (Holt’s) | 0.9940 | 0.9930 | 0.6760 | 0.9990 | 0.9900 | 0.9350 | 0.9920 | 0.9540 | 0.6920 | 1.0000 | 0.9990 | 0.9970 |
R-squared (ULFR) | 0.9970 | 0.9677 | 0.8331 | 0.9997 | 0.9950 | 0.9595 | 0.9986 | 0.9770 | 0.7621 | 0.9999 | 0.9993 | 0.9983 |
NSE (Holt’s) | 0.9875 | 0.9257 | 0.5635 | 0.9997 | 0.9999 | 0.9994 | 1.0000 | 1.0000 | 1.0000 | 0.9999 | 0.9999 | 0.9996 |
NSE (ULFR) | 0.9934 | 0.9959 | 0.9407 | 0.9997 | 1.0000 | 0.9997 | 1.0000 | 1.0000 | 1.0000 | 0.9999 | 1.0000 | 0.9997 |
MFE (Holt’s) | 0.0814 | 0.2725 | 0.6606 | 0.0162 | 0.0102 | 0.0251 | 0.0010 | 0.0014 | 0.0032 | 0.0112 | 0.0073 | 0.0188 |
MFE (ULFR) | 0.0814 | 0.0637 | 0.2435 | 0.0159 | 0.0039 | 0.0180 | 0.0010 | 0.0010 | 0.0022 | 0.0111 | 0.0057 | 0.0178 |
