本文選題：自回歸 + 季節(jié)性��； 參考：《現(xiàn)代預(yù)防醫(yī)學(xué)》2016年16期

【摘要】：目的探索分析手足口病周數(shù)據(jù)的統(tǒng)計(jì)學(xué)方法,提升手足口病預(yù)測(cè)能力。方法中國(guó)疾病預(yù)防控制信息系統(tǒng)導(dǎo)出2008年第1周至2014年第14周北京市通州區(qū)手足口病周發(fā)病數(shù)。采用SPSS 17.0軟件進(jìn)行自回歸、季節(jié)性自回歸與混合Serfling回歸模型擬合。結(jié)果自回歸、季節(jié)性自回歸、混合Serfling回歸3種模型對(duì)2008年第1周至2014年第14周實(shí)際發(fā)病數(shù)進(jìn)行擬合,回歸方程R2分別是0.907、0.917、0.919,所得殘差經(jīng)Ljung-Box檢驗(yàn)均是白噪聲;以所得回歸方程對(duì)2014年第15周至第38周實(shí)際發(fā)病數(shù)進(jìn)行預(yù)測(cè),3種模型的平均絕對(duì)百分比誤差(MAPE)分別為:18.67%、18.43%、17.12%。結(jié)論混合Serfling回歸模型預(yù)測(cè)效果最優(yōu)。
[Abstract]:Objective to explore the statistical method of analyzing the week data of hand, foot and mouth disease (HFMD) in order to improve the predictive ability of HFMD. Methods from the first week of 2008 to the 14th week of 2014, the incidence of hand, foot and mouth disease in Tongzhou District of Beijing was derived from China Disease Prevention and Control Information system. The software SPSS 17.0 was used to carry out autoregressive, seasonal autoregressive and mixed Serfling regression models. Results autoregressive, seasonal autoregressive and mixed Serfling regression models were used to fit the actual incidence from the first week of 2008 to the 14th week of 2014. The regression equation R2 was 0.9070.917 ~ 0.919, respectively. The residual errors were all white noise by Ljung-Box test. According to the regression equation, the average absolute percentage error (MAPE) of the three models for predicting the actual incidence from week 15 to week 38 of 2014 is: 1: 18.67 and 18.43 and 17.12 respectively. Conclusion the mixed Serfling regression model has the best prediction effect.
【作者單位】： 北京市通州區(qū)疾病預(yù)防控制中心;
【分類號(hào)】：R725.1;R181.3
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本文編號(hào)：1874955