组合预测建模中单项预测模型筛选研究

Research on single forecast model screening for combination forecast modeling

组合预测模型本身是一个对单项预测模型的信息进行选择利用的过程。分析了如何判定和检验参与组合预测的单项预测需满足何种条件,并运用了协整理论对模型进行筛选,从三方面综合地提出了筛选组合预测单项模型的方法和步骤,以期提高组合预测精度,简化计算。在初选的单项预测模型中,除选用较为常见的预测方法外,还加入了一些具有代表性的的单项预测方法,如状态空间模型、神经网络模型等。这些良好预测模型的选用,在一定程度上提高了组合预测的精度。

Combination forecast modeling is essentially a process that selects and makes use of the information gained through single forecast models. How to make judgment about the conditions that the single forecast model should meet is analysed. Moreover, the co-integration theory is applied to screen models, and a compre- hensive method is proposed to screen the single forecast model for combination forecast modeling in three aspects so as to improve forecast precision and simplify computation. In the initial single forecast model, some repre- sentative single forecast methods, such as state space models and neural networks, are adopted except for the common forecast methods. The adoption of these fine forecast models improves the precision of combination forecast to a certain extent.