Preference orderings assigned by coherent lower and upper conditional previsions are defined and they are considered to define maximal random variables and Bayes random variables. Sufficient conditions are given such that a random variable is maximal if and only if it is a Bayes random variable. In a metric space preference orderings represented by coherent lower and upper conditional previsions defined by Hausdorff inner and outer measures are given. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Preference orderings represented by coherent upper and lower conditional previsions

Serena Doria
2019

Abstract

Preference orderings assigned by coherent lower and upper conditional previsions are defined and they are considered to define maximal random variables and Bayes random variables. Sufficient conditions are given such that a random variable is maximal if and only if it is a Bayes random variable. In a metric space preference orderings represented by coherent lower and upper conditional previsions defined by Hausdorff inner and outer measures are given. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11564/703797
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