摘要
目的构建广州市白纹伊蚊密度自回归积分移动平均模型(ARIMA)并进行预测。方法应用R语言3.4.4将2009年1月至2017年5月的白纹伊蚊月密度数据构建ARIMA模型,进行整体回代评价拟合效果,比较2017年6-12月预测值与真实值,评价外推效果,对2018年白纹伊蚊密度进行预测。结果白纹伊蚊密度监测数据构建ARIMA(0,1,1)(0,1,1)12模型,赤池信息准则(AIC)=-268.83,平稳R2=0.427;残差序列为白噪声(P>0.05),且方差齐性,证明模型有效;2017年6-12月预测值与实际值基本一致,均方根误差(RMSE)=0.087 4,平均绝对误差(MAE)=0.028 3,模型外推良好。结论 ARIMA模型能够较好地预测广州市白纹伊蚊密度消长趋势。
Objective To construct the autoregressive integrated moving average (ARIMA)model to predict by summarizing the density data ofAedes albopictus in Guangzhou.Methods Through the R programming language 3.4.4,the model was constituted by density of Ae.albopictus from January 2009 to June 2017,proceeded significance test of model and parameter,and evaluated the model by overall data.the predicted value and the real value from July to December 2017 were compared to evaluate the extrapolation effect.Results ARIMA (0,1,1)(0,1,1)12 has been constituted with AIC=-268.83 and R^2=0.427.Residual sequence was proved white noise (P>0.05)and homoscedasticity.The predicted value and the real value from July to December 2017 are approximately in agreement,showing the Root Mean Square Error (RMSE)=0.087 4 and the Mean Absolute Error (MAE)=0.028 3.Good data fit was demonstrated.Conclusion The model can well predict the density data of Ae.albopictus in Guangzhou.
作者
潘衍宇
吴海霞
国佳
刘起勇
PAN Yan-yu;WU Hai-xia;GUO Jia;LIU Qi-yong(State Key Laboratory of Infectious Disease Prevention and Control,National Institute for Communicable Disease Control and Prevention,Chinese Center for Disease Control and Prevention,Collaborative Innovation Center for Diagnosis and Treatment of lnfectious Diseases,WHO Collaborating Centre for Vector Surveillance and Management,Beijing 102205,China)
出处
《中国媒介生物学及控制杂志》
CAS
2018年第6期545-549,共5页
Chinese Journal of Vector Biology and Control
基金
国家重点研发计划(2016YFC1200802)
国家重大科学研究计划(2012CB955504)~~
关键词
时间序列
自回归积分移动平均模型
白纹伊蚊
预测
Time series analysis
Autoregressive integrated moving average model
Aedes albopictus
Prediction
