系统发生树的置信集
Confidence sets for phylogenetic trees
摘要：
推断进化历史（系统发育树）在生物学、犯罪学和公共卫生方面有重要的应用。然而，系统发育树是复杂的数学对象，驻留在非欧几里德空间中，这使其分析复杂化。虽然我们的数学，算法和概率的理解，在他们的度量空间是成熟的，严格的推理基础设施尚未开发。在这篇手稿中，我们统一了最近的计算和概率的进步，构建树值置信集。该程序占中心和多个方向的树值的变化。我们利用区块复制来改进测试，确定最佳支持的寨卡病毒最近的祖先，并正式测试佛罗里达州一名患有艾滋病的牙医感染了他的两名患者艾滋病毒的假设。该方法说明了欧氏空间和树空间的变异之间的连接，开放系统发育树分析技术，可在多变量欧氏设置。
英文摘要：
Inferring evolutionary histories (phylogenetic trees) has important applications in biology, criminology and public health. However, phylogenetic trees are complex mathematical objects that reside in a non-Euclidean space, which complicates their analysis. While our mathematical, algorithmic, and probabilistic understanding of phylogenies in their metric space is mature, rigorous inferential infrastructure is as yet undeveloped. In this manuscript we unify recent computational and probabilistic advances to construct tree--valued confidence sets. The procedure accounts for both centre and multiple directions of tree--valued variability. We draw on block replicates to improve testing, identifying the best supported most recent ancestor of the Zika virus, and formally testing the hypothesis that a Floridian dentist with AIDS infected two of his patients with HIV. The method illustrates connections between variability in Euclidean and tree space, opening phylogenetic tree analysis to techniques available in the multivariate Euclidean setting.
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