Table 2.

Summary of AICc (for training data), RMSE (for test data) and RC values for different models calculated based on the epidemic data of six provinces/cities in China.

	Heilongjiang			Tianjin			Hunan			Guangdong			Chongqing			Xiaogan
Model	AICc	RMSE	RC	AICc	RMSE	RC	AICc	RMSE	RC	AICc	RMSE	RC	AICc	RMSE	RC	AICc	RMSE	RC
Hill’s	5.9	16	0.62	3.58	69	0.79	6.09	122	0.67	6.76	447	0.42	7.42	61	0.83	10.71	73	0.66
Logistic	5.26	46	0.89	3.48	15	0.78	7.43	178	0.89	6.09	113	0.90	6.74	75	0.82	10.17	363	0.90
Gompertz’s	5.87	112	0.53	3.36	20	0.45	6.16	18	0.86	6.55	719	0.58	6.15	29	0.71	10.57	240	0.69
Richards’	6.08	101	0.92	3.61	62	0.78	6.47	132	0.93	6.86	105	0.71	6.47	77	0.88	10.79	623	0.93
G-Logistic	5.23	79	0.78	3.58	47	0.01	6.00	76	0.39	6.40	98	0.57	5.70	314	0.01	10.28	481	0.79
Exp.Growth	6.21	34	0.85	3.55	6.6	0.60	7.92	28	0.89	6.43	41	0.86	6.96	46	0.80	10.96	322	0.95
Max.LLH	7.21	283	0.31	4.04	57	0.11	8.80	475	0.56	7.82	698	0.54	7.43	260	0.40	11.73	3.1e3	0.72
Seq.Bayes.	5.30	27	0.08	3.36	7	0.65	8.87	176	0.57	7.53	434	0.02	6.50	68	0.44	10.86	242	0.58
TimeDep.	5.50	71	0.72	3.29	17	0.05	8.49	279	0.88	6.08	43	0.62	7.00	126	0.82	10.04	296	0.88
SIR	6.75	2.1e3	0.94	3.45	161	0.99	8.13	3.2e3	0.92	7.78	1.9e4	0.93	5.25	666	0.98	11.56	8.3e3	0.99
SEIR	6.98	2.1e3	0.78	3.66	169	0.68	8.55	3.1e3	0.44	8.11	2.1e4	0.30	5.58	390	0.47	11.69	6.8e3	0.65
SEIR-QD	3.13	6.8	0.90	3.15	7.0	0.86	4.27	25	0.77	5.52	107	0.76	3.15	7.0	0.88	5.86	156	0.76
SEIR-AHQ	9.38	38	0.81	7.84	17	0.37	13.80	336	0.66	13.84	351	0.57	12.03	138	0.42	15.07	601	0.38
SEIR-PO	4.56	29	0.78	4.20	19	0.63	5.50	85	0.71	6.32	217	0.60	4.42	24	0.73	6.18	185	0.84