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Regional summaries of Bayesian model uncertainty

Li, Hanqing et al.
arXiv (All) · Papers
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62f1565c0590c27g-3i-2-6machine-learningmethodology
Bayesian posterior uncertainty can be spread across many models that share the same substantive pattern. Lists of individual models can obscure this structure, while marginal summaries do not describe which configurations are jointly supported. We study how to represent joint model uncertainty throu
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