@misc{Hua20,
    author = { Zhuoqun Huang and Ronald L. Rivest and Philip B. Stark and Vanessa Teague and Damjan Vukcevic },
    title = { A Unified Evaluation of Two-Candidate Ballot-Polling Election Auditing Methods },
    date = { 2020-08-19 },
    howpublished = { (arXiv:2008.08536) },
    urla =        { <a href="https://arxiv.org/abs/2008.08536">arXiv</a> },
    OPTyear = { 2020 },
    OPTmonth = { August 19, },
    abstract = {
    Counting votes is complex and error-prone. Several statistical methods have been developed to
    assess election accuracy by manually inspecting randomly selected physical ballots.
    Two 'principled' methods are risk-limiting audits (RLAs) and Bayesian audits (BAs).
    RLAs use frequentist statistical inference while BAs are based on Bayesian inference.
    Until recently, the two have been thought of as fundamentally different.
    We present results that unify and shed light upon 'ballot-polling' RLAs and BAs (which
    only require the ability to sample uniformly at random from all cast ballot cards)
    for two-candidate plurality contests, the are building blocks for auditing more
    complex social choice functions, including some preferential voting systems.
    We highlight the connections between the methods and explore their performance.
    First, building on a previous demonstration of the mathematical equivalence of classical
    and Bayesian approaches, we show that BAs, suitably calibrated, are risk-limiting.
    Second, we compare the efficiency of the methods across a wide range of contest
    sizes and margins, focusing on the distribution of sample sizes
    required to attain a given risk limit. Third, we outline several ways to
    improve performance and show how the mathematical equivalence explains the improvements.
    }                  
}