Inferential models predict unobserved auxiliary values via calibrated predictive random sets before transferring plausibility to parameters, yielding valid uncertainty statements that relate fiducial, confidence, and belief-function approaches.
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Inferential Models: The Power of Auxiliary Variables for Reasoning with Scientific Uncertainty
Inferential models predict unobserved auxiliary values via calibrated predictive random sets before transferring plausibility to parameters, yielding valid uncertainty statements that relate fiducial, confidence, and belief-function approaches.