Concentration functions and Bayesian robustness. (With discussion)

DOI10.1016/0378-3758(94)90121-XzbMath0799.62031OpenAlexW2068439858MaRDI QIDQ1333140

Sandra Fortini, Fabrizio Ruggeri

Publication date: 13 October 1994

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(94)90121-x

zbMATH Keywords

concentration functionBayesian robustnessrepresentation theoremsextremal measuresLorenz curveposterior robustnesscomparing probability measuresepsilon contaminationsmixtures of probability measuresneighbourhood classes of probability measuresprior and posterior expectations

Mathematics Subject Classification ID

Bayesian inference (62F15) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (5)

An overview of robust Bayesian analysis. (With discussion) ⋮ Robust Bayesian analysis given priors on partition sets ⋮ Concentration function and sensitivity to the prior ⋮ Symmetric, coherent, Choquet capacities ⋮ Bayesian Forecasting for Accident Proneness Evaluation

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• Robust Bayesian analysis: sensitivity to the prior
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• On solutions of minimax test problems for special capacities
• An Approach to Robust Bayesian Analysis for Multidimensional Parameter Spaces
• Inequalities: theory of majorization and its applications

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