In this paper we consider Bayesian-like inference processes involving coherent $T$-conditional possibilities assessed on infinite sets of conditional events. For this, a characterization of coherent assessments of possibilistic prior and likelihood is carried on. Since we are working in a finitely maxitive setting, the notions of complete disintegrability and of complete conglomerability are also studied and their relevance in the infinite version of the possibilistic Bayes formula is highlighted.

Bayesian-like inference, complete disintegrability and complete conglomerability in coherent conditional possibility theory

COLETTI, Giulianella;PETTURITI, DAVIDE
2013

Abstract

In this paper we consider Bayesian-like inference processes involving coherent $T$-conditional possibilities assessed on infinite sets of conditional events. For this, a characterization of coherent assessments of possibilistic prior and likelihood is carried on. Since we are working in a finitely maxitive setting, the notions of complete disintegrability and of complete conglomerability are also studied and their relevance in the infinite version of the possibilistic Bayes formula is highlighted.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1128472
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