ARIMA模型在疟疾发病率预测中的应用 |
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引用本文: | 夏菁,张华勋,林文,裴速建,孙凌聪,董小蓉,曹慕民,吴冬妮,蔡顺祥. ARIMA模型在疟疾发病率预测中的应用[J]. 中国血吸虫病防治杂志, 2016, 28(2): 135-140 |
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作者姓名: | 夏菁 张华勋 林文 裴速建 孙凌聪 董小蓉 曹慕民 吴冬妮 蔡顺祥 |
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作者单位: | 湖北省疾病预防控制中心血吸虫病防治研究所 (武汉430079) |
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摘 要: | 目的 目的 应用自回归求和移动平均模型 (Autoregressive Integrated Moving Average Model, ARIMA) 进行湖北省本地疟疾发病率预测。 方法 方法 应用SPSS 13.0软件对2004-2009年湖北省本地疟疾发病率构建ARIMA模型, 并以2010年发病率数据检验模型, 评价模型拟合及预测效果。 结果 结果 经检验确认ARIMA (1,1,1) (1,1,0) 12模型拟合效果相对最优, AIC=76.085, SBC=84.395, 发病率实际值均在预测值的95%可信区间内, 表明模型预测效果较好。 结论 结论 ARIMA模型可对湖北省本地疟疾发病率进行较好的拟合和预测。
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关 键 词: | 疟疾 时间序列 ARIMA模型 预测 发病率 |
Application of ARIMA model on prediction of malaria incidence |
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Affiliation: | Institute of Schistosomiasis Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China |
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Abstract: | Objective Objective To predict the incidence of local malaria of Hubei Province applying the Autoregressive IntegratedMoving Average model(ARIMA) . Methods Methods SPSS 13.0 software was applied to construct the ARIMA model based on themonthly local malaria incidence in Hubei Province from 2004 to 2009. The local malaria incidence data of 2010 were used formodel validation and evaluation. Results Results The model of ARIMA(1,1,1)(1,1,0) 12 was tested as relatively the best optimalwith the AIC of 76.085 and SBC of 84.395. All the actual incidence data were in the range of 95% CI of predicted value of themodel. The prediction effect of the model was acceptable. Conclusion Conclusion The ARIMA model could effectively fit and predict theincidence of local malaria of Hubei Province. |
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Keywords: | Malaria Time series ARIMA model Prediction Incidence |
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