Confidence Sets for Phylogenetic Trees

@article{Willis2016ConfidenceSF,
  title={Confidence Sets for Phylogenetic Trees},
  author={Amy D. Willis},
  journal={Journal of the American Statistical Association},
  year={2016},
  volume={114},
  pages={235 - 244}
}
  • A. Willis
  • Published 2016
  • Mathematics, Biology
  • Journal of the American Statistical Association
ABSTRACT 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… Expand
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