Combination Forecasting Models Using Regression Analysis Method

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.

Combination Forecasting Models Using Regression Analysis Method

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.