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.
Distance metrics for ranked evolutionary trees.Proc
2 Pith papers cite this work, alongside 27 external citations. Polarity classification is still indexing.
2
Pith papers citing it
27
external citations · OpenAlex
years
2026 2verdicts
UNVERDICTED 2representative citing papers
New triangular matrix representations and matrix-norm distances for comparing rooted ranked unlabeled phylogenetic networks.
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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.
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Matrix representations and distance metrics for unlabeled ranked phylogenetic networks
New triangular matrix representations and matrix-norm distances for comparing rooted ranked unlabeled phylogenetic networks.