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Optimal Statistical Hypothesis Testing for Social Choice
Published 19 Jun 2020 in math.ST, cs.AI, cs.GT, and stat.TH | (2006.11362v1)
Abstract: We address the following question in this paper: "What are the most robust statistical methods for social choice?'' By leveraging the theory of uniformly least favorable distributions in the Neyman-Pearson framework to finite models and randomized tests, we characterize uniformly most powerful (UMP) tests, which is a well-accepted statistical optimality w.r.t. robustness, for testing whether a given alternative is the winner under Mallows' model and under Condorcet's model, respectively.
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