Multiple Priors as Similarity Weighted Frequencies
Jürgen Eichberger and
Ani Guerdjikova ()
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Ani Guerdjikova: Cornell University, Department of Economics
No 470, Working Papers from University of Heidelberg, Department of Economics
In this paper, we consider a decision-maker who tries to learn the distribution of outcomes from previously observed cases. For each observed sequence of cases the decision-maker predicts a set of priors expressing his beliefs about the underlying probability distribution. We impose a version of the concatenation axiom introduced in BILLOT, GILBOA, SAMET AND SCHMEIDLER (2005) which insures that the sets of priors can be represented as a weighted sum of the observed frequencies of cases. The weights are the uniquely determined similarities between the observed cases and the case under investigation.
Pages: 39 pages
Date: 2008-07, Revised 2008-07
New Economics Papers: this item is included in nep-upt
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Working Paper: Multiple Priors as Similarity Weighted Frequencies (2008)
Working Paper: Multiple Priors as Similarity Weighted Frequencies (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:awi:wpaper:0470
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