论文标题
使用Dirichlet-Tree模型进行审计排名的投票选举：第一步
Auditing Ranked Voting Elections with Dirichlet-Tree Models: First Steps
论文作者
论文摘要
排名的投票系统，例如Instant-Runoff投票（IRV）和单一可转让投票（STV），在全球许多地方都使用。它们比多元化和评分规则更复杂，对审核其结果提出了挑战：除全手数外，没有其他STV的限制风险审计方法（RLA）方法。 我们提出了一种使用统计模型，即Dirichlet-Tree的新方法，该方法可以以计算有效的方式应对高维参数。我们通过对IRV选举进行投票审理的贝叶斯审计来证明这种方法。尽管该技术尚不为风险限制，但我们建议一些策略可以允许将其校准以限制风险。
Ranked voting systems, such as instant-runoff voting (IRV) and single transferable vote (STV), are used in many places around the world. They are more complex than plurality and scoring rules, presenting a challenge for auditing their outcomes: there is no known risk-limiting audit (RLA) method for STV other than a full hand count. We present a new approach to auditing ranked systems that uses a statistical model, a Dirichlet-tree, that can cope with high-dimensional parameters in a computationally efficient manner. We demonstrate this approach with a ballot-polling Bayesian audit for IRV elections. Although the technique is not known to be risk-limiting, we suggest some strategies that might allow it to be calibrated to limit risk.
