Mathematical Models for Statistical Decision Theory
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WISCONSIN UNIV-MADISON MATHEMATICS RESEARCH CENTER
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Three methods of defining optimality of statistical decision rules are introduced. The first uses ideas of approximation theory by defining the optimal decision as that element of the risk set which best approximates an ideal rule. The second optimality principle defines optimality in terms of minimizing functionals. The third method is the axiomatization of optimality in statistical decision theory.
- Statistics and Probability