郑州大学学报（医学版）2018，Vol.53Issue(1)：79-84,6.DOI:10.13705/j.issn.1671-6825.2017.20.027
基于ARIMA乘积季节模型和Holt-Winters季节模型的梅毒月发病率预测
Application of seasonal model of ARIMA and Holt-Winters in prediction of the monthly incidence of syphilis
摘要
Abstract
Aim:To explore the application value of ARIMA and Holt-Winters seasonal model for predicting the monthly incidence of syphilis.Methods:SPSS 22.0 and Eviews 8.0 were used to establish the seasonal model of ARIMA and Holt-Winters based on the data of the monthly incidence of syphilis in China from January 2005 to December 2015.Then the actual data from January to June in 2016 were used to confirm the predicted results.The prediction evaluation index was error and MAE.The data from July to December in 2016 were forcasted by the model with higher precision in the similar manner.Results:In the comparison of MAE,the prediction accuracy of the seasonal ARIMA model was higher than the Holt-Winters seasonal model.The optimal model for the monthly incidence was ARIMA (1,1,1) × (0,1,1) 12,the model equation was (1-B)(1-B12)(1 +0.374B)x1 =(1 +0.740B)(1 +0.775B12)ε1.The predicted results of the monthly incidence of syphilis(1/100 000) from July to December in 2016 were 3.107,2.989,2.879,2.658,2.631,2.644.Conclusion:The seasonal ARIMA model features higher predictive accuracy,and could agree well with the trend of the monthly incidence of syphilis.关键词
梅毒/ARIMA/Holt-Winters/月发病率Key words
syphilis/ARIMA/the Holt-Winters/the monthly incidence分类
医药卫生引用本文复制引用
马晓梅,史鲁斌,其木格,闫国立,施学忠,孙春阳,徐学琴,赵倩倩..基于ARIMA乘积季节模型和Holt-Winters季节模型的梅毒月发病率预测[J].郑州大学学报（医学版）,2018,53(1):79-84,6.基金项目
国家“十二·五”科技重大专项(2012ZX10004905) （2012ZX10004905）
河南省医学科技攻关计划项目(201303003) （201303003）
