Please use this identifier to cite or link to this item:
Eichberger, Jürgen
Guerdjikova, Ani
Year of Publication: 
Series/Report no.: 
Discussion Paper Series 470
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.
Document Type: 
Working Paper

Files in This Item:
419.65 kB

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.