桂林电子科技大学学报2012，Vol.32Issue(5)：410-415,6.
基于ARIMA模型的时间序列建模算法和实证分析
Modeling algorithm and empirical analysis based on the time series of the ARIMA model
摘要
Abstract
Through the study of time series ARIMA model modeling method, this paper applies variance analysis to time series modeling, after which carries out relevant variance tests on season datas and finally ascertains their cycle. Based on the detailed specific algorithm of statistical software SAS on analysing the ARIMA model modeling methods, as well as its specific steps on drafting particular flow chart. This paper elaborates the overall process of the model establishment and its forecast from those various aspects such as the model identification, the parameter estimation and the modeling establishment and its forecast. Finally, it uses the SAS software which combines with the incoming variance testing method and the algorithm process to establish the product ARIMA model on Chinese consumer price index of the seasonal time sequence from January 1990 to December 2010, forecast and analyze the basic trend of the CPI.关键词
时间序列/ARIMA模型/季节模型/预测/方差分析/算法/CPIKey words
time series/ ARIMA model/ seasonal model) forecast/ variance analysis/ algorithm/ CPI分类
数理科学引用本文复制引用
赵肖肖,朱宁,黄黎平..基于ARIMA模型的时间序列建模算法和实证分析[J].桂林电子科技大学学报,2012,32(5):410-415,6.基金项目
广西区"十一五"教学改革工程项目(GX06066) （GX06066）
