Data-based decisions under imprecise probability and least favorable models
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Publication:962888
DOI10.1016/j.ijar.2008.03.009zbMath1185.62021OpenAlexW2119539277MaRDI QIDQ962888
Publication date: 7 April 2010
Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ijar.2008.03.009
decision theoryrobust statisticsimprecise probabilitycoherent upper previsionequivalence of modelsHuber-Strassen theoryLe Camleast favorable model
Bayesian problems; characterization of Bayes procedures (62C10) Minimax procedures in statistical decision theory (62C20) Statistical decision theory (62C99)
Related Items (2)
Information efficient learning of complexly structured preferences: elicitation procedures and their application to decision making under uncertainty ⋮ Finite approximations of data-based decision problems under imprecise probabilities
Cites Work
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- Decision making under uncertainty using imprecise probabilities
- Statistical decision theory and Bayesian analysis. 2nd ed
- Asymptotic methods in statistical decision theory
- Least favorable pairs for special capacities
- The theory of interval-probability as a unifying concept for uncertainty
- Neyman-Pearson testing under interval probability by globally least favorable pairs: Reviewing Huber-Strassen theory and extending it to general interval probability
- Minimax tests and the Neyman-Pearson lemma for capacities
- On the construction of least favourable pairs of distributions
- Statistical experiments and their conical measures
- Simultaneously least favorable experiments
- Sufficiency and Approximate Sufficiency
- Γ-Minimax: A Paradigm for Conservative Robust Bayesians
- Minimax Theorems
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