Abstract
This chapter discusses parallel structure between duality relationships for the linear functional version of the generalized Neyman–Pearson problem. The duality relationships are developed by establishing the equivalence of the dual problem to a Lagrangian dual problem, which is related to the generalized Neyman–Pearson problem in a known manner. The duality theory of linear programming as it applies to the bounded variable linear programming problem is applicable, with appropriate modifications, to the fundamental generalized Neyman–Pearson problem of statistics. The adoption of a linear programming point of view permits insights that would perhaps not be obtained otherwise into the generalized Neyman–Pearson problem.
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