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。
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.
出处
《长春工业大学学报》
CAS
2006年第2期96-99,共4页
Journal of Changchun University of Technology
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
ARIMA model
white noise series
auto-regessive
moving average
autocorrelation
partial correlation.
