Application of ARIMA model in predicting monthly incidence of syphilis
10.7652/jdyxb201801028
- VernacularTitle:基于ARIMA模型预测梅毒月发病率的价值
- Author:
mei Xiao MA
1
;
qin Xue XU
;
li Guo YAN
;
zhong Xue SHI
;
Ying LIU
;
jin Jin WANG
;
hui Xiao LIU
;
ying Lan PEI
Author Information
1. 河南中医药大学公共卫生与预防学科
- Keywords:
syphilis;
autoregressive integrated moving average model (ARIMA);
monthly incidence;
prediction
- From:
Journal of Xi'an Jiaotong University(Medical Sciences)
2018;39(1):131-134,152
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the value of the autoregressive integrated moving average model (ARIMA) applied to predict monthly incidence of syphilis so as to provide basis for prevention and control of syphilis . Methods Eviews 8 .0 was used to establish the ARIMA model based on the data of monthly incidence of syphilis in China from January 2009 to December 2015 .Then the data of the first half of 2016 were used to verify the predicted results .The predictions were evaluated by RMSE ,MAE ,MAPE and MRE models .Then the monthly incidence of syphilis in the second half of 2016 was predicted .Results The optimal model for the monthly incidence of syphilis from January 2009 to June 2016 was the model of ARIMA (2 ,1 ,1) × (0 ,1 ,1)12 ,its equation was (1 - B)(1 - B12 ) (1+0 .820 B)(1+0 .566 B2 ) x2t = (1+0 .365 B) (1+0 .897 B12 )εt ,its parameters are as follows :R2 =0 .832 ,RMSE=0 .181 ,MAE=0 .118 ,MAPE=5 .088 .The predicted monthly incidence values (10-5 ) of the second half of 2016 were 3 .124 ,3 .008 ,2 .906 ,2 .691 ,2 .714 ,and 2 .717 .Conclusion ARIMA model has a relatively good prediction precision .Therefore , it can make short-term prediction based on the evolution trend of monthly incidence of syphilis in China .
