Epidemic Situation of Brucellosis in Jinzhou City of China and Prediction Using the ARIMA Model

Table 1

Parameter estimation of 8 candidate models.

	B	SE	t
ARIMA(1,1,1)(0,1,0)12
AR1	0.59	0.09	6.92	0.00
MA1	0.99	0.17	5.91	0.00
ARIMA(1,1,1)(0,1,1)12
AR1	0.55	0.11	5.16	0.00
MA1	0.93	0.06	15.59	0.00
SMA1	0.71	0.12	5.99	0.00
ARIMA(1,1,1)(1,1,0)12
AR1	0.54	0.11	4.86	0.00
MA1	0.92	0.06	15.71	0.00
SAR1	−0.45	0.09	−5.14	0.00
ARIMA(1,1,1)(1,1,1)12
AR1	0.55	0.11	5.21	0.00
MA1	0.93	0.06	15.66	0.00
SAR1	0.09	0.18	0.48	0.63
SMA1	0.78	0.22	3.63	0.00
ARIMA(2,1,1)(0,1,0)12
AR1	0.61	0.10	6.11	0.00
AR2	−0.02	0.10	−0.15	0.88
MA1	0.99	0.15	6.86	0.00
ARIMA(2,1,1)(0,1,1)12
AR1	0.55	0.11	5.00	0.00
AR2	0.00	0.11	−0.01	0.99
MA1	0.93	0.07	14.13	0.00
SMA1	0.71	0.12	5.95	0.00
ARIMA(2,1,1)(1,1,0)12
AR1	0.54	0.11	4.76	0.00
AR2	0.02	0.11	0.22	0.83
MA1	0.93	0.06	14.90	0.00
SAR1	−0.45	0.09	−5.14	0.00
ARIMA(2,1,1)(1,1,1)12
AR1	0.55	0.11	5.03	0.00
AR2	−0.01	0.11	−0.08	0.94
MA1	0.93	0.07	13.98	0.00
SAR1	0.09	0.18	0.49	0.63
SMA1	0.78	0.22	3.61	0.00

Note. The parameter estimation of the ARIMA(1,1,1)(0,1,0)₁₂, ARIMA(1,1,1)(0,1,1)₁₂, and ARIMA(1,1,1)(1,1,0)₁₂ models showed , but for other models, .