赛晓勇,张治英,徐德忠,闫永平,李良寿,蔡凯平,李岳生,周晓农.不同时间序列分析法在洞庭湖区血吸虫病发病预测中的比较[J].中华流行病学杂志,2004,25(10):863-866 |
不同时间序列分析法在洞庭湖区血吸虫病发病预测中的比较 |
Application of "time series analysis" in the prediction of schistosomiasis prevalence in areas of "breaking dikes or opening sluice for waterstore" in Dongting Lake areas, China |
收稿日期:2003-09-29 出版日期:2014-09-18 |
DOI: |
中文关键词: 血吸虫病|时间序列分析|统计预测 |
英文关键词: Schistosomiasis|Time series analysis|Statistical prediction |
基金项目:国家“十五”科技攻关课题资助项目(2001BA705B08) |
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中文摘要: |
目的 通过比较时间序列分析中指数平滑法、移动平均法、自回归分析及自回归综合移动平均法(ARIMA)在洞庭湖区退田还湖濠口试点1990~2002年血吸虫病患病率预测中的优劣。方法 用时间序列分析各方法建模预测,比较各方法1994~2002年预测值的误差平方和,确定最佳预测方法。结果 指数平滑法、移动平均法、自相关分析及ARIMA法中1994~2002年预测值的误差平方和依次为39.40、39.86、26.63、22.54。结论 濠口试点1990~2002年患病率预测中,时间序列分析诸方法中ARIMA模型预测效果较好。 |
英文摘要: |
Objective To provide the fittest model for forecasting schistosomiasis prevalence in Haokou village of "breaking dikes or opening sluice for waterstore" in Dongting Lake areas by comparing the Results of Moving Average, Exponential Smoothing, Autoregressive Model and Autoregressive integrated moving average model (ARIMA model) from 1990 to 2002. Methods Error sum of square of four statistical Methods was compared and the fittest model was chosen. Results Error sum of square of predicted schistosomiasis prevalence rates in Haokou village from 1994 to 2002 were 39.40,39.86, 26.63, 22.54 respectively. Conclusion ARIMA model seemed to be the fittest one in the prediction of schistosomiasis prevalence in Haokou village of "breaking dikes or opening sluice for waterstore" in Dongting Lake from 1990 to 2002. |
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