Admissible decision rule

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Bayesian statistics
Posterior = Likelihood × Prior ÷ Evidence
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In statistical decision theory, an admissible decision rule is a rule for making a decision such that there is no other rule that is always "better" than it^[1] (or at least sometimes better and never worse), in the precise sense of "better" defined below. This concept is analogous to Pareto efficiency.