摘要
目的探讨乘法季节回归求和移动平均模型(ARIMA)在安徽省细菌性痢疾预测中应用,为细菌性痢疾的预测提供参考。方法根据2010~2015年每月细菌性痢疾发病数据,运用R软件拟合乘法季节性ARIMA模型,并对2016年细菌性痢疾的发病数进行预测。结果安徽省细菌性痢疾预测最优模型为ARIMA(0,1,0)×(0,1,1)12模型,残差统计量检验差异无统计学意义(Ljung-Box=12.812,P=0.383),提示残差为白噪声,模型拟合值与实际值平均绝对误差百分比为10.30%,2015年1~12月预测值和实际值平均绝对误差百分比为11.89%。结论建立的乘法季节ARIMA模型能很好地拟合安徽省细菌性痢疾的变动趋势,模型预测效果较好,可用于安徽省细菌性痢疾发病短期预测。
Objective To explore the application of multiple seasonal autoregressive integrated moving average model in predicting bacillary dysentery incidence in Anhul province,and provide evidence for the forecast and early warning of bacillary dysentery. Methods According to the 2010~2015 year data of monthly bacillary dysentery in Anhui province,R software was used to fit the multiplicative seasonal ARIMA model,and the number of bacillary dysentery in 2016 was predicted. Results Multiple seasonal ARIMA（ 0,1,0 ） X（ 0,1,1 ） 12 was established for the pre- diction of bacillary dysentery incidence in Anhui province. There was no significance in Ljung-Box Q（ Ljung-Box Q= 12. 812,P = 0. 383）and residuals was the white noise. The average absolute percentage error between fitted and value actual was 10.30%. The average absolute error percentage of the predicted and actual values from January to De- cember 2015 was 11.89~. Conclusion The ARIMA model fitting effects are well and suitable to short-term predic- tion of bacillary dysentery incidence in Anhui province.
作者
张进
陈国平
曹明华
马婉婉
ZHANG Jin;CHEN Guoping;CAO Minghua;MA Wanwan(Anhui Provincial Center for Disease Control and Preven-tion,Hei fei 230601,Anhui,China)
出处
《安徽预防医学杂志》
2018年第5期343-345,353,共4页
Anhui Journal of Preventive Medicine
关键词
细菌性痢疾
乘积季节ARIMA模型
传染病预测
Bacillary dysentery
Multiple seasonal ARIMA Model
Infectious disease prediction
