We model an individual who wants to learn about a state of the world. The individual has a prior belief and has data that consist of multiple forecasts about the state of the world. Our key assumption is that the decision maker identifies explanations that could have generated this data and among these focuses on those that maximize the likelihood of observing the data. The decision maker then bases her final prediction about the state on one of these maximum likelihood explanations. We show that in all the maximum likelihood explanations, moderate forecasts are just statistical derivatives of extreme ones. Therefore, the decision maker will base her final prediction only on the information conveyed in the relatively extreme forecasts. We show that this approach to combining forecasts leads to a unique prediction, and a simple and dynamically consistent way to aggregate opinions.

中文翻译：

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组合预测的最大似然方法

我们为想要了解世界状况的个人建模。个人有一个先验信念，并拥有由多个关于世界状况的预测组成的数据。我们的关键假设是决策者确定了可能产生这些数据的解释，其中重点关注那些最大限度地提高观察数据的可能性的解释。然后，决策者将她对状态的最终预测基于这些最大似然解释之一。我们表明，在所有最大似然解释中，中等预测只是极端预测的统计衍生物。因此，决策者的最终预测只会基于相对极端的预测所传达的信息。我们表明，这种组合预测的方法会产生独特的预测，