摘要
提出了基于AR并将其推广到CAR模型对时间序列统一建模的新观点和方法,并以实例对动态模型与静态模型分别作了应用比较。结果表明,时间序列分析动态模型预测精度高,用途广泛。
Based on AR model and its extension to CAR model, this paper presents a new method for centralized modeling for time series. Dynamic model and static model are compared. The result shows that the dynamic model of time series analysis is an important system analysis and an advanced forecast one among statistics forecast method. Its forecast precision is high. Static model is suitable for interposition.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2005年第6期483-487,共5页
Geomatics and Information Science of Wuhan University
关键词
动态模型
静态模型
预测
dynamic model
static model
forecast
