Statistical sufficiency formalizes the notion of data reduction. In the decision theoretic interpretation, once a model is chosen all inferences should be based on a sufficient statistic. However, suppose we start with a set of procedures rather than a specific model. Is it possible to reduce the data and yet still be able to compute all of the procedures? In other words, what functions of the data contain all of the information sufficient for computing these procedures? This article presents so...
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