摘要
目的探讨自回归求和移动平均(autoregressive integrated moving average,ARIMA)季节乘积模型在季节性时间序列资料分析中的应用,建立结核病发病率的预测模型。方法利用重庆市结核病防治所登记的某区1993至2004年结核病新发病例数及该区各年的平均人口数,采用条件最小二乘法估计模型参数,按照残差不相关原则、简洁原则确定模型的结构,依据 Akaike 信息准则(Akaike's information criterion,AIC)与 Schwartz 的贝叶斯信息准则(Bayesian information criterion,BIC)确定模型的阶数,建立结核病发病率 ARIMA 季节乘积预测模型。结果非季节和季节移动平均参数分别为0.84076和0.46602,t 检验的 P 值均小于0.05,有统计学意义,方差估计值为0.088589,AIC=19.75979,SBC=23.28219,显示模型提取序列中几乎所有的样本相关信息。对模型进行残差白噪声分析,x^2检验统计量的 P 值均大于0.05,表明 ARIMA(0,1,1)(0,1,1)_4NOINT 模型是有效的。结论 ARIMA(0,1,1)(0,1,1)_4NOINT 模型是一种短期内预测精度较高的结核病发病率预测模型。
Objective To discuss the application of multiple seasonal autoregressive integrated moving average （ARIMA） predictive model of time series and to establish a predictive incidence model of tuberculosis. Methods Parameters of the model were estimated using conditional least squares method according to the data of tuberculosis incidence and the averaged population in a district in Chongqing from 1993 to 2004. In a structure determined according to criteria of residual un-correlation and concision, ARIMA predictive model was established and the order of model was confirmed by Akaike＇s Information Criterion（AIC, for short） and Schwartz＇ s Bayesian Information Criterion （ SBC or BIC, for short）. Results There were significant differences of the fitted multiple seasonal moving-average coefficients with the nonseasonal and the seasonal moving-average coefficients being 0. 84076 and 0. 46602 respectively. The estimated variance was 0.088589, AIC = 19. 75979, SBC = 23. 28219. Autocorrelation check of residuals of model was white-noise residual. ARIMA（0,1,1 ） （0,1,1）4NOINT seemed to be the most appropriate model by X^2 test. Conclusion The multiple seasonal ARIMA model can be used to forecast for tuberculosis incidence with high prediction and precision in a short-term.
出处
《中华预防医学杂志》
CAS
CSCD
北大核心
2007年第2期118-121,共4页
Chinese Journal of Preventive Medicine
关键词
模型
统计学
结核
时间因素
发病率
预测
Models
Statistical study
Tuberculosis
Time factors
Incidence
Forecasting
作者简介
通讯作者：王润华，Email：wzhzyp@163．com
