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Neyman-Scott is a classic example of an estimation problem with apartially-consistent posterior, for which standard estimation methods tend toproduce inconsistent results. Past attempts to create consistent estimators forNeyman-Scott have led to ad-hoc solutions, to estimators that do not satisfyrepresentation invariance, to restrictions over the choice of prior and more.We present a simple construction for a general-purpose Bayes estimator,invariant to representation, which satisfies consistency on Neyman-Scott overany non-degenerate prior. We argue that the good attributes of the estimatorare due to its intrinsic properties, and generalise beyond Neyman-Scott aswell.

RKL: a general, invariant Bayes solution for Neyman-Scott