Partial probabilistic information
Abstract Suppose a decision maker (DM) has partial information about certain events of a [sigma]-algebra belonging to a set and assesses their likelihood through a capacity v. When is this information probabilistic, i.e. compatible with a probability? We consider three notions of compatibility with a probability in increasing degree of preciseness. The weakest requires the existence of a probability P on such that P(E)>=v(E) for all , we then say that v is a probability lower bound. A stronger one is to ask that v be a lower probability, that is the infimum of a family of probabilities on . The strongest notion of compatibility is for v to be an extendable probability, i.e. there exists a probability P on which coincides with v on . We give necessary and sufficient conditions on v in each case and, when is finite, we provide effective algorithms that check them in a finite number of steps.
Year of publication: |
2011
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Authors: | Chateauneuf, Alain ; Ventura, Caroline |
Published in: |
Journal of Mathematical Economics. - Elsevier, ISSN 0304-4068. - Vol. 47.2011, 1, p. 22-28
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Publisher: |
Elsevier |
Keywords: | Partial probabilistic information Exact capacity Core Extensions of set functions |
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