Vague Credence.

It is natural to think of precise probabilities as being special cases of imprecise probabilities, the special case being when one's lower and upper probabilities are equal. I argue, however, that it is better to think of the two models as representing two different aspects of our credences, which a...

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Published in:Synthese Vol. 194; no. 10; pp. 3931 - 3955
Main Author: Lyon, Aidan
Format: Article
Published: Springer Nature Oct2017
Subjects:
Online Access:View this record in EBSCOhost
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        10.1007/s11229-015-0782-5
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        Probability theory
        Mathematics
        Statistical decision making
        Vagueness (Philosophy)
        Vagueness doctrine (Constitutional law)
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          Probability theory
          Mathematics
          Statistical decision making
          Vagueness (Philosophy)
          Vagueness doctrine (Constitutional law)
      keyword:
        Aggregation
        Credence
        Degree of belief
        Imprecise
        Indeterminate
        Subjective probability
        Vagueness
      ab: It is natural to think of precise probabilities as being special cases of imprecise probabilities, the special case being when one's lower and upper probabilities are equal. I argue, however, that it is better to think of the two models as representing two different aspects of our credences, which are often (if not always) vague to some degree. I show that by combining the two models into one model, and understanding that model as a model of vague credence, a natural interpretation arises that suggests a hypothesis concerning how we can improve the accuracy of aggregate credences. I present empirical results in support of this hypothesis. I also discuss how this modeling interpretation of imprecise probabilities bears upon a philosophical objection that has been raised against them, the so-called inductive learning problem.
      pubtype: Academic Journal
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      src: R
    language: English
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