A comparison of state space and multiple regression for monthly forecasts: U.S. Fuel consumption
A comparison of state space and multiple regression for monthly forecasts: U.S. Fuel consumption
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月度预测的状态空间和多元回归比较：美国燃料消耗
DOI：
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发表时间：
1995
期刊：
影响因子：
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通讯作者：
D. Harris
中科院分区：
文献类型：
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作者：
Kyungcho. Bae;D. Harris
美国石油、天然气和煤炭的月度消费预测使用状态空间和应用于相同数据的多元回归。这些预测与测试期间的实际消费量进行比较。对于暴露和扩展情况，使用状态空间进行的预测优于使用多元回归模型进行的预测。状态空间预测比回归预测更能跟踪数据周期。状态空间模型的平均绝对预测误差小于多元回归模型。
Monthly consumption forecasts for U.S. oil, natural gas, and coal are made using state space and multiple regression applied to the same data. These forecasts are compared with actual consumption for a test period. The forecasts made using state space are preferred to those made using multiple regression models for both expost and exante cases. The state space forecasts track data cycles better than do the regression forecasts. Average absolute forecast errors are less for the state space models than they are for the multiple regression models.