Admissibility and its opposite inadmissibility are two notions used in game theory and in statistical decision theory to evaluate estimators. An inadmissible estimator is dominated everywhere by another estimator, hence should not be used (if the domination criterion is relevant for the problem at hand). Wald in the 1950’s showed that the admissible estimators are more or less the Bayes estimators. This is covered in Chapter 3 of The Bayesian Choice.

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