The IM interval is the shortest valid prior-free procedure for the Behrens-Fisher problem, established via cylindrical predictive random sets, minimaxity, admissibility, and a projection argument.
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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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Revisiting the Behrens-Fisher Problem: Validity-First Optimality
The IM interval is the shortest valid prior-free procedure for the Behrens-Fisher problem, established via cylindrical predictive random sets, minimaxity, admissibility, and a projection argument.
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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.