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Decision-making with possibilistic inferential models
Ryan Martin, Shih-Ni Prim, Jonathan Williams
Inferential models (IMs) are data-dependent, imprecise-probabilistic structures designed to quantify uncertainty about unknowns. As the name suggests, the focus has been on uncerta…
math.ST2025
Asymptotic efficiency of inferential models and a possibilistic Bernstein--von Mises theorem
Ryan Martin, Jonathan P. Williams
The inferential model (IM) framework offers an alternative to the classical probabilistic (e.g., Bayesian and fiducial) uncertainty quantification in statistical inference. A key d…