Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control · 2013
[Prediction of hookworm incidence with time-series model in Jiangsu Province].
Аннотация на английскомСтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Jiang Wen-Cai, Jin Xiao-Lin, Shen Ming-Xue, Cao Han-Jun, Xu Xiang-Zhen
Аннотация
OBJECTIVE: To explore the feasibility of autoregressive integrated moving average (ARIMA) to predict the infection rates of hookworm in Jiangsu Province.
METHODS: From 1990 to 2006, the infection rates of hookworm were used for a training data set. As to obtain a stationary data set, the training data set was second-order differenced using the version SAS 9.0. The model parameters were screened by using the minimum information criterion. The ARIMA model was constructed to predict the infect rates of hookworm form 2007 to 2011.
RESULTS: The time-series model ARIMA (1, 2, 0) was confirmed preliminarily. The model fitted well the training data set. The predictive infection rates were main accordance with the actual status of hookworm from 2007 to 2011, and the most minimum error was only 9.23%.
CONCLUSION: The model constructed has a good predictive effect and applied value for control of hookworm.
METHODS: From 1990 to 2006, the infection rates of hookworm were used for a training data set. As to obtain a stationary data set, the training data set was second-order differenced using the version SAS 9.0. The model parameters were screened by using the minimum information criterion. The ARIMA model was constructed to predict the infect rates of hookworm form 2007 to 2011.
RESULTS: The time-series model ARIMA (1, 2, 0) was confirmed preliminarily. The model fitted well the training data set. The predictive infection rates were main accordance with the actual status of hookworm from 2007 to 2011, and the most minimum error was only 9.23%.
CONCLUSION: The model constructed has a good predictive effect and applied value for control of hookworm.