Concentration inequality for evolutionary trees

Abstract : Maximum likelihood inferred topologies are commonly used to draw conclusions in evolutionary biology and molecular evolution. Considering the sampling error when estimating the topology is a critical issue. Bootstrap-based methods are the most popular tools to assess the robustness of clades, i.e. the stability of a tree and subtrees. Unfortunately, there is no analytical result to connect the bootstrap values to the sampling variability, or at least to the number of sites and species in the study. Using concentration measure tools, we first bound the variations of the computed likelihood around its true value and then bound the sampling variability of likelihood as measured by bootstrap. In particular and unlike most bootstrap-based methods, these bounds are explicitly sensitive to both the number of species and of nucleotides.
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Journal of Multivariate Analysis, Elsevier, 2009, pp.2055-2064. <10.1016/j.jmva.2009.02.015>
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https://hal.archives-ouvertes.fr/hal-00410872
Contributeur : Avner Bar-Hen <>
Soumis le : lundi 24 août 2009 - 23:41:47
Dernière modification le : mardi 11 octobre 2016 - 13:27:57

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Mahendra Mariadassou, Avner Bar-Hen. Concentration inequality for evolutionary trees. Journal of Multivariate Analysis, Elsevier, 2009, pp.2055-2064. <10.1016/j.jmva.2009.02.015>. <hal-00410872>

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