A Markov embedding of ranked unlabelled trees reduces state space, enabling efficient Fréchet means, arbitrary-order F-matrix moments via phase-type theory, and improved neutrality tests under coalescent models.
Employing phylogenetic tree shape statistics to resolve the underlying host population structure.BMC Bioinformatics22 (2021).https://doi.org /10.1186/s12859-021-04465-1
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Markov embedding of ranked unlabelled evolutionary trees and its applications
A Markov embedding of ranked unlabelled trees reduces state space, enabling efficient Fréchet means, arbitrary-order F-matrix moments via phase-type theory, and improved neutrality tests under coalescent models.