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
2019-01-01
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.File in questo prodotto:
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