In statistical decision theory, an admissible decision rule is a rule for making a decision such that there isn't any other rule that is always "better" than it.
Generally speaking, in most decision problems the set of admissible rules is large, even infinite, so this is not a sufficient criterion to pin down a single rule, but as will be seen there are some good reasons to favor admissible rules; compare Pareto efficiency.
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