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组合预测模型的回归分析方法
引用本文:谢开贵,周家启.组合预测模型的回归分析方法[J].重庆大学学报(自然科学版),2003,26(1):62-65.
作者姓名:谢开贵  周家启
作者单位:重庆大学电气工程学院 重庆400044 (谢开贵),重庆大学电气工程学院 重庆400044(周家启)
基金项目:重庆大学青年骨干教师资助基金
摘    要:给出求解组合预测权系数的回归分析方法,文章首先给出了基于最小二乘和最小一乘准则的线性回归组合预测模型,然后应用最小二乘原理得到权系数最小二乘估计值。由于最小一乘准则下,目标函数不可微,传统的优化规则方法无法求解,故文中提出用基于最小二乘的逐步变权方法进行求解。同时,还给出了百分误差绝对值最小为目标的组合预测模型及权系数求解方法。通过实例分析,表明组合预测模型的预测精度很高,回归效果很显著。

关 键 词:回归分析方法  组合预测模型  最小二乘准则  最小一乘准则  逐步变权法  组合预测权系数
文章编号:1000-582X(2003)01-0062-04
修稿时间:2002年9月10日

Combination Forecasting Models Using Regression Analysis Method
XIE Kai? gui,ZHOU Jia? qi.Combination Forecasting Models Using Regression Analysis Method[J].Journal of Chongqing University(Natural Science Edition),2003,26(1):62-65.
Authors:XIE Kai? gui  ZHOU Jia? qi
Abstract:Using regression analysis method,the methods for solving the weights of combination forecasting model(CFM) are proposed. At first, the linear regress CFM are presented based on the least absolute criteria and least square criteria. Then the weights can be evaluated using the least square princinple. Because the objective function of CFM based on least absolute criteria is non differential, the traditional programming methods can not solve it. So the least square method with the modified weights is proposed to solve this problem. At the same time, methods for solving CFM is given with the aim of minimizing sum of percentage error absolutes. From many cases, the results show that the forecasting precision of CFM is very high and the effect of regression is remarkable.
Keywords:combination forecasting model  least square criteria  least absolute criteria  method of the modified weights step by step
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