Finite approximations of data-based decision problems under imprecise probabilities

DOI10.1016/J.IJAR.2009.05.003zbMath1185.62022OpenAlexW1998927957MaRDI QIDQ962921

Robert Hable

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.2009.05.003

zbMATH Keywords

discretizationimprecise probabilitycoherent lower previsiondata-based decision theory

Mathematics Subject Classification ID

Statistical decision theory (62C99)

Related Items (2)

A minimum distance estimator in an imprecise probability model -- computational aspects and applications ⋮ Minimum distance estimation in imprecise probability models

Cites Work

• Data-based decisions under imprecise probability and least favorable models
• Finite approximations to coherent choice
• Decision making under uncertainty using imprecise probabilities
• Statistical decision theory and Bayesian analysis. 2nd ed
• Asymptotic methods in statistical decision theory
• Maxmin expected utility with non-unique prior
• The theory of interval-probability as a unifying concept for uncertainty
• Direct algorithms for checking consistency and making inferences from conditional probability assessments
• A survey of the theory of coherent lower previsions
• Minimax tests and the Neyman-Pearson lemma for capacities
• Optimal decisions under complex uncertainty – basic notions and a general algorithm for data‐based decision making with partial prior knowledge described by interval probability
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