From Conditional Events to Conditional Measures: A New Axiomatic Approach
Annals of Mathematics and Artificial Intelligence
Possibility theory and statistical reasoning
Computational Statistics & Data Analysis
Conditional probability and fuzzy information
Computational Statistics & Data Analysis
Inference with fuzzy and probabilistic information
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
Generalized Bayesian inference in a fuzzy context: From theory to a virtual reality application
Computational Statistics & Data Analysis
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Without a clear, precise and rigorous mathematical frame, is the likelihood "per se" a proper tool to deal with statistical inference and to manage partial and vague information? Since (as Basu puts it) "the likelihood function is after all a bunch of conditional probabilities", a proper discussion of the various extensions of a likelihood from a point function to a set function is carried out by looking at a conditional probability as a general non-additive "uncertainty" measure P (E | · ) on the set of conditioning events.