Imprecise probability generalizes probability theory to allow for partial probability specifications, and is applicable when information is scarce, vague, or conflicting, in which case a unique probability distribution may be hard to identify. Thereby, the theory aims to represent the available knowledge more accurately. Imprecision is useful for dealing with expert elicitation, because:
People have a limited ability to determine their own subjective probabilities and might find that they can only provide an interval.
As an interval is compatible with a range of opinions, the analysis ought to be more convincing to a range of different people.
and 25 Related for: Imprecise probability information
Impreciseprobability generalizes probability theory to allow for partial probability specifications, and is applicable when information is scarce, vague...
This allows one to study possibility theory using the tools of impreciseprobabilities. We call generalized possibility every function satisfying Axiom...
probabilities without dependence assumptions. Bounding probabilities has continued to the present day (e.g., Walley's theory of impreciseprobability...
(2007). Impreciseprobability methods for sensitivity analysis in engineering. Proceedings of the 5th International Symposium on ImpreciseProbability: Theories...
Society for ImpreciseProbability: Theories and Applications (SIPTA) was created in February 2002, with the aim of promoting the research on Imprecise probability...
the subsequent development of 'modern Bayesian probability', and the notion of impreciseprobabilities is now well established in statistics, with a wide...
In impreciseprobability theory, the Choquet integral is also used to calculate the lower expectation induced by a 2-monotone lower probability, or the...
understood connections to other frameworks such as probability, possibility and impreciseprobability theories. These theoretical frameworks can be thought...
Society for ImpreciseProbability (SIPTA) in 2019, he was invited to deliver a talk on "Game-theoretic foundations for impreciseprobabilities" in Belgium...
Moreover, a-posteriori, it assigns zero probability to any set that does not include the observations. The imprecise Dirichlet process has been proposed to...
introduction to the imprecise Dirichlet model for multinomial data. Tutorial for the Third International Symposium on ImpreciseProbabilities and Their Applications...
general method in probabilities, focusing on determining the consequent probability of events logically connected to given probabilities. His work was expanded...
Words of estimative probability (WEP or WEPs) are terms used by intelligence analysts in the production of analytic reports to convey the likelihood of...
derive, or imprecise. With the aid of Retrosheet, however, win probability added has become substantially easier to calculate. The win probability for a specific...
a results of such calculations we will get so called impreciseprobability. Impreciseprobability is understood in a very wide sense. It is used as a generic...
Upper and lower probabilities are representations of impreciseprobability. Whereas probability theory uses a single number, the probability, to describe...
Sanders Peirce. Levi was known for his work in belief revision and impreciseprobability. Levi, Isaac (1973) [1967]. Gambling with truth: an essay on induction...
specializes in formal epistemology. Much of his work has focused on impreciseprobability. He is currently Professor of Philosophy and Computer Science at...
[citation needed] Impreciseprobability Dempster–Shafer theory Probability box Robust Bayes analysis Upper and lower probabilities Levi, I. (1980). The...
based on impreciseprobability. Credal networks can be regarded as an extension of Bayesian networks, where credal sets replace probability mass functions...
probabilities. The agent then tries to satisfice the expected utility and maximize the robustness against uncertainty in the impreciseprobabilities....
Bayesian probability Bayesian programming Bayesianism Checking if a coin is fair Conjugate prior Factor graph Good–Turing frequency estimation Imprecise probability...
"Information Processing under Imprecise Risk with the Hurwicz criterion" (PDF). International Symposium on ImpreciseProbability: Theories and Applications...
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