The Application of the Prediction of the Reported Weekly Incidence of Bacillary Dysentery in Chaoyang District Using the Time Series Model
10.3969/j.issn.1002-3674.2009.06.007
- VernacularTitle:时间序列分解法在北京市朝阳区细菌性痢疾周报告发病率预测中的应用
- Author:
Shufeng CUI
;
Jianxin MA
;
Shuming LI
- Publication Type:Journal Article
- Keywords:
Bacillary dysentery;
Time series;
Auto regressive integrated moving average(ARIMA) model;
Prediction
- From:
Chinese Journal of Health Statistics
2009;(6):583-585,591
- CountryChina
- Language:Chinese
-
Abstract:
Objective The study estabfished a model to pre-dict the weekly incidence of bacillary dysentery in Chaoyang District,and evaluated its predictive effects. Methods To eliminate the factors of sea-son-changing by means of Time Series. Auto regressive integrated moving average(ARIMA), based on model identification, estimation andverifica-tion of parameter, and analysis of the fitting of model, was established. Fi-nally,the predictive model was established by the multiple of ARLMA and seasonal factors. Results The error of the model for the prediction was -0.06 on average. The relative error was 2.32% on average. Conclusion Time series could not only accurately predict useing the data which was collected every week,but shorten the cycle of prediction.
