Finitely maxitive conditional possibilities, Bayesian-like inference, disintegrability and conglomerability

DOI10.1016/j.fss.2015.09.025zbMath1383.62060OpenAlexW2190791031MaRDI QIDQ1699332

Davide Petturiti, Giulianella Coletti

Publication date: 19 February 2018

Published in: Fuzzy Sets and Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.fss.2015.09.025

zbMATH Keywords

coherence\(T\)-conditional possibilityconglomerabilitydisintegrabilityBayesian-like inferencefinite maxitivitypossibilistic likelihood function

Mathematics Subject Classification ID

Bayesian inference (62F15) Axioms; other general questions in probability (60A05) Parametric inference and fuzziness (62F86)

Related Items (9)

The integrated sigma-max system and its application in target recognition ⋮ Basic ideas underlying conglomerability and disintegrability ⋮ Fuzzy memberships as likelihood functions in a possibilistic framework ⋮ Envelopes of conditional probabilities extending a strategy and a prior probability ⋮ Qualitative conditioning in an interval-based possibilistic setting ⋮ Coherent T-conditional Possibility Envelopes and Nonmonotonic Reasoning ⋮ Coherent checking and updating of Bayesian models without specifying the model space: a decision-theoretic semantics for possibility theory ⋮ Decision Rules Under Vague and Uncertain Information ⋮ Finitely maxitive \(T\)-conditional possibility theory: coherence and extension

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