| 欧亚商都购物人次时间序列预测模型 |
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| 引用本文： | 刘丹.欧亚商都购物人次时间序列预测模型[J].吉林工学院学报,2006,27(2):96-99. |
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| 作者姓名： | 刘丹 |
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| 作者单位： | 长春工业大学基础科学学院 吉林长春130012，上海财经大学应用数学系，上海200439 |
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| 摘 要： | 时间序列分析是一种根据动态数据揭示系统动态结构和规律的统计方法,文中采用1998~2002年的数据,应用时间序列分析中的ARIMA模型对欧亚商都2003~2004年的季节购物人次进行了预测,实际计算过程由Eviews软件的自回归移动平均模型ARIMA过程实现,结果与实际数据基本相符,本模型所取参数对欧亚商都购物人次的短期预测是行之有效的。
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| 关 键 词： | ARIMA模型 白噪声序列 自回归 移动平均 自相关 偏自相关 |
| 文章编号： | 1006-2939（2006）02-0096-04 |
| 收稿时间： | 2005-03-31 |
| 修稿时间： | 2005年3月31日 |
Time series models for the number of customers in Ouya Department Store |
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| LIU Dan.Time series models for the number of customers in Ouya Department Store[J].Journal of Jilin Institute of Technology,2006,27(2):96-99. |
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| Authors: | LIU Dan |
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| Institution: | 1. School of Basic Sciences, Changchun University of Technology, Changchun 130012, China; 2. Department of Mathematics, Shanghai University of Finance and Economics, Shanghai 200429, China |
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| Abstract: | Time series analysis is an important branch in statistics.It reveals the system constructures and rules according to the dynamic data.The basic thought here is to select accurately the models(reflecting) the dynamic dependent relations in time series according to the finite running records((observed) data) and to forecast the coming system run.This paper applies ARIMA Model to forecast the number of custmers in Ouya Department Store.The practical results is run with Eviews. |
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| Keywords: | ARIMA model white noise series auto-regessive moving average autocorrelation (partial) correlation |
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