| ARIMA乘积季节模型在青州市布鲁氏菌病发病预测中的应用 |
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| 引用本文： | 刘杰,武钦发,李伟国,肖宇飞,毛倩,石福艳,王素珍.ARIMA乘积季节模型在青州市布鲁氏菌病发病预测中的应用[J].中国医院统计,2020(2):97-100,105. |
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| 作者姓名： | 刘杰 武钦发 李伟国 肖宇飞 毛倩 石福艳 王素珍 |
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| 作者单位： | 山东省青州市地方病防治研究所;山东省青州市疾病预防控制中心;潍坊医学院卫生统计学教研室 |
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| 基金项目： | 国家自然科学基金项目(81803337,81872719);国家统计局基金项目(2018LY79);山东省自然科学基金项目(ZR201807090257);潍坊医学院博士启动基金项目(2017BSQD51);潍坊医学院扶贫基金项目(FP1801001)。 |
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| 摘 要： | 目的应用自回归求和移动平均(ARIMA)乘积季节模型预测青州市布鲁氏菌病月发病数,构建青州市布鲁氏菌病月发病数的预测模型,为青州市布鲁氏菌病防控措施提供科学依据。方法收集青州市2011—2017年布鲁氏菌病监测数据,采用SPSS 25.0统计软件建立ARIMA时间序列模型,并对模型进行检验,预测出2018年的布鲁氏菌病月发病数,用2018年布鲁氏菌病实际月发病数评价模型的预测效果。结果模型ARIMA(0,1,1)(1,1,0)12标准化的BIC值最小,Box-Ljung检验统计量Q=23.746,P>0.05,残差序列为白噪声,确定为最优模型。结论ARIMA乘积季节模型短期预测青州市布鲁氏菌病月发病数效果较好。
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| 关 键 词： | ARIMA模型 布鲁氏菌病 月发病数 预测 |
Application of multiple seasonal ARIMA model in forecasting the incidence of brucellosis in Qingzhou |
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| Liu Jie,Wu Qinfa,Li Weiguo,Xiao Yufei,Mao Qian,Shi Fuyan,Wang Suzhen.Application of multiple seasonal ARIMA model in forecasting the incidence of brucellosis in Qingzhou[J].Chinese Journal of Hospital Statistics,2020(2):97-100,105. |
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| Authors: | Liu Jie Wu Qinfa Li Weiguo Xiao Yufei Mao Qian Shi Fuyan Wang Suzhen |
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| Institution: | (Qingzhou Institute of Endemic Disease Prevention and Control, Qingzhou 262500, China;Qingzhou Disease Prevention and Control Center, Qingzhou 262500,China;Department of Health Statistics, School of Public Health and Management, Weifang Medical University, Weifang 261053, China) |
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| Abstract: | Objective To predict the monthly incidence of brucellosis in Qingzhou by multiple seasonal ARIMA model of autoregressive integrated moving average(ARIMA),and to construct a prediction model for the monthly incidence of brucellosis in Qingzhou so as to provide scientific basis for prevention and control measures of brucellosis in Qingzhou.Methods The monitoring data of brucellosis in Qingzhou from 2011 to 2017 were collected,ARIMA time series model was established with SPSS 25.0 statistical software,the model was tested to predict the monthly incidence of brucellosis in 2018,and the prediction effect of the model was evaluated by the actual monthly incidence of brucellosis in 2018.Results The normalized BIC value of ARIMA(0,1,1)(1,1,0)12 model is the smallest,the Box-Ljung test statistic is as follows:Q=23.746,P>0.05,the residual sequence is white noise,thus it is determined to be the optimal model.Conclusion Multiple seasonal ARIMA model is effective in short-term prediction of monthly incidence of brucellosis in Qingzhou. |
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| Keywords: | ARIMA model brucellosis monthly incidence forecast |
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