Optimal Statistical Hypothesis Testing for Social Choice
Statistics Theory
2020-06-23 v1 Artificial Intelligence
Computer Science and Game Theory
Statistics Theory
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.
Cite
@article{arxiv.2006.11362,
title = {Optimal Statistical Hypothesis Testing for Social Choice},
author = {Lirong Xia},
journal= {arXiv preprint arXiv:2006.11362},
year = {2020}
}