| 摘要 |
A method to select causal factors to be used within a causal product demand forecasting framework. The methodology determines the set of factors that have statistically significant effects on historical product demand, and hence are believed to be of greatest relevance in determining product demand changes in the future. The effects of all factors are determined simultaneously and the net effect of each variable is calculated. When several factors are operative at the same time, the net influence of each factor is calculated. Lesser and redundant factors in the causal forecasting model can be eliminated to improve the stability, scalability and efficiency of the model. The method is employed to optimize causal models to achieve maximum forecast accuracy.
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