To combine or not to combine? Issues of combining forecasts
To combine or not to combine? Issues of combining forecasts
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DOI：
10.1002/for.3980110806
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发表时间：
1992-12
影响因子：
3.4
通讯作者：
F. Palm;A. Zellner
中科院分区：
文献类型：
--
作者：
F. Palm;A. Zellner
本文讨论的问题，如：它总是支付联合收割机个人预测的一个变量？联合收割机是否应该将一个无偏预测与一个严重偏差的预测结合起来？我们是否应该使用贝茨和格兰杰20多年前提出的最佳权重？提出了一个简单的模型，占个人预测的主要特点。贝叶斯分析的模型，使用非信息和信息先验概率密度提供了扩展和推广的结果，温克勒（1981），并与非贝叶斯方法相结合的预测，明确依赖于一个统计模型的个人预测。它表明，在某些情况下，它是明智的，而不是使用贝茨和格兰杰型权重使用一个简单的平均个人预测。最后，模型的不确定性被认为是不同的模型相结合的个人预测的问题得到解决。
This paper addresses issues such as: Does it always pay to combine individual forecasts of a variable? Should one combine an unbiased forecast with one that is heavily biased? Should one use optimal weights as suggested by Bates and Granger over twenty years ago? A simple model which accounts for the main features of individual forecasts is put forward. Bayesian analysis of the model using noninformative and informative prior probability densities is provided which extends and generalizes results obtained by Winkler (1981) and compared with non-Bayesian methods of combining forecasts relying explicitly on a statistical model for the individual forecasts. It is shown that in some instances it is sensible to use a simple average of individual forecasts instead of using Bates and Granger type weights. Finally, model uncertainty is considered and the issue of combining different models for individual forecasts is addressed.