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Ambiguity, data and preferences for information -A case-based approach

机译:歧义,数据和信息偏好-基于案例的方法

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摘要

We model decision making under ambiguity based on available data. Decision makers express preferences over actions and data sets. We derive an a-max-min representation of preferences, in which beliefs combine objective characteristics of the data (number and frequency of observations) with subjective features of the decision maker (similarity of observations and perceived ambiguity). We identify the subjectively perceived ambiguity and separate it into ambiguity due to a limited number of observations and ambiguity due to data heterogeneity. The special case of no ambiguity provides a behavioral foundation for beliefs as similarity-weighted frequencies as in Billot et al. (2005) [3].
机译:我们根据可得数据在模棱两可的情况下对决策建模。决策者对行动和数据集表示偏爱。我们推导了偏好的a-max-min表示,其中信念将数据的客观特征(观察的数量和频率)与决策者的主观特征(观察的相似性和感知的歧义性)结合在一起。我们识别出主观感知到的歧义,并由于数量有限的观察而将其分为歧义,并且由于数据异质性而将歧义分为歧义。无歧义的特殊情况为信念提供了行为基础,例如Billot等人的相似加权频率。 (2005)[3]。

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