| 基于ARIMA模型的新冠肺炎序列分析预测 |
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| 引用本文： | 纪安之,杨雪梅.基于ARIMA模型的新冠肺炎序列分析预测[J].价值工程,2020,39(18):107-109. |
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| 作者姓名： | 纪安之 杨雪梅 |
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| 作者单位： | 咸阳师范学院数学与信息科学学院,咸阳712000;咸阳师范学院数学与信息科学学院,咸阳712000 |
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| 摘 要： | 利用国家卫生健康委公开的2020年1月24日24时至2020年3月29日24时新冠肺炎累计确诊病例数据,采用时间序列分析方法建立ARIMA模型进行拟合分析,并预测其未来走势。用SAS软件编程,结果表明,原序列2阶差分后为平稳非白噪声序列,ARIMA(0,2,1)模型可以较好地拟合原序列,并通过了模型的显著性检验和参数的显著性检验。未来5日的预测结果与实际数据吻合较好。
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| 关 键 词： | 新型冠状病毒肺炎 时间序列 ARIMA 预测 SAS |
Analysis and Prediction of Time Series of 2019-nCoV Based on ARIMA Model |
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| JI An-zhi,YANG Xue-mei.Analysis and Prediction of Time Series of 2019-nCoV Based on ARIMA Model[J].Value Engineering,2020,39(18):107-109. |
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| Authors: | JI An-zhi YANG Xue-mei |
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| Institution: | (College of Mathematics and Information Science,Xianyang Normal University,Xianyang 712000,China) |
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| Abstract: | Using the data of 2019-nCoV pneumonia cumulative diagnosis from 24:00 on January 24,2020 to 24:00 on March 29,2020,the ARIMA model was established by time series analysis to analyze the trend and predict the future trend.The results show that the original sequence is a stationary non white noise sequence after the second-order difference,ARIMA(0,2,1)model can fit the original sequence well and pass the significance test of the model and the significance test of the parameters.The predicted results in the next five days are in good agreement with the actual data. |
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| Keywords: | 2019-nCoV time series ARIMA prediction SAS |
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