Multiple Decision Rules for Comparing Several Populations with a Fixed Known Standard.
CORNELL UNIV ITHACA N Y DEPT OF OPERATIONS RESEARCH
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Independent observations are available from k univariate distributions indexed by a real parameter theata. It is desired to select that distribution with the largest parameter value unless this value is smaller than some fixed standard theata sub 0 in which case no distribution is to be selected. Various single-stage procedures for this k1-decision problem are discussed, using indifference zone, decision theoretic, Bayesian, and subset selection approaches.
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