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Phylogenetic trees summarize evolutionary relationships. The Billera-Holmes-Vogtmann (BHV) space for comparing phylogenetic trees has many elegant mathematical properties, but it does not encompass trees with differing leaf sets. To…

Populations and Evolution · Quantitative Biology 2025-08-12 Maria Alejandra Valdez Cabrera , Amy D Willis

The phylogenetic tree space introduced by Billera, Holmes, and Vogtmann (BHV tree space) is a CAT(0) continuous space that represents trees with edge weights with an intrinsic geodesic distance measure. The geodesic distance measure unique…

Quantitative Methods · Quantitative Biology 2021-10-29 Yingying Ren , Sihan Zha , Jingwen Bi , José A. Sanchez , Cara Monical , Michelle Delcourt , Rosemary K. Guzman , Ruth Davidson

The metric space of phylogenetic trees defined by Billera, Holmes, and Vogtmann, which we refer to as BHV space, provides a natural geometric setting for describing collections of trees on the same set of taxa. However, it is sometimes…

Populations and Evolution · Quantitative Biology 2018-07-12 Gillian Grindstaff , Megan Owen

Phylogenetic trees are hybrid objects: branch lengths vary continuously, while topologies change discretely through edge contractions and expansions. Billera-Holmes-Vogtmann (BHV) tree space provides a canonical geometry for this structure,…

Populations and Evolution · Quantitative Biology 2026-05-22 Yasha Ektefaie , Leo Cui , Shrey Jain , Marinka Zitnik , Pardis Sabeti

We revise the Levy's construction of Brownian motion as a simple though still rigorous approach to operate with various Gaussian processes. A Brownian path is explicitly constructed as a linear combination of wavelet-based "geometrical…

Statistical Mechanics · Physics 2020-01-03 Denis S. Grebenkov , Dmitry Beliaev , Peter W. Jones

Fractional Brownian motion is a self-affine, non-Markovian and translationally invariant generalization of Brownian motion, depending on the Hurst exponent $H$. Here we investigate fractional Brownian motion where both the starting and the…

Statistical Mechanics · Physics 2016-11-09 Mathieu Delorme , Kay Jörg Wiese

We observe $n$ sequences at each of $m$ sites, and assume that they have evolved from an ancestral sequence that forms the root of a binary tree of known topology and branch lengths, but the sequence states at internal nodes are unknown.…

Computation · Statistics 2014-08-28 Adam Persing , Ajay Jasra , Alexandros Beskos , David Balding , Maria De Iorio

We propose a new space of phylogenetic trees which we call wald space. The motivation is to develop a space suitable for statistical analysis of phylogenies, but with a geometry based on more biologically principled assumptions than…

Probability · Mathematics 2020-09-21 Maryam K. Garba , Tom M. W. Nye , Jonas Lueg , Stephan F. Huckemann

Cubical complexes are metric spaces constructed by gluing together unit cubes in an analogous way to the construction of simplicial complexes. We construct Brownian motion on such spaces, define random walks, and prove that the transition…

Populations and Evolution · Quantitative Biology 2019-05-23 Tom M. W. Nye

We consider a directed random walk making either 0 or $+1$ moves and a Brownian bridge, independent of the walk, conditioned to arrive at point $b$ on time $T$. The Hamiltonian is defined as the sum of the square of increments of the bridge…

Condensed Matter · Physics 2016-08-31 Servet Martinez , Dimitri Petritis

The Billera-Holmes-Vogtmann (BHV) space of weighted trees can be embedded in Euclidean space, but the extrinsic Euclidean mean often lies outside of treespace. Sturm showed that the intrinsic Frechet mean exists and is unique in treespace.…

It has been observed that the sample mean of certain probability distributions in Billera-Holmes-Vogtmann (BHV) phylogenetic spaces is confined to a lower-dimensional subspace for large enough sample size. This non-standard behavior has…

Statistics Theory · Mathematics 2023-04-12 Lars Lammers , Do Tran Van , Tom M. W. Nye , Stephan F. Huckemann

This paper proposes a novel framework for manifold-valued regression and establishes its consistency as well as its contraction rate. It assumes a predictor with values in the interval $[0,1]$ and response with values in a compact…

Statistics Theory · Mathematics 2015-07-27 Xu Wang , Gilad Lerman

Inferential summaries of tree estimates are useful in the setting of evolutionary biology, where phylogenetic trees have been built from DNA data since the 1960's. In bioinformatics, psychometrics and data mining, hierarchical clustering…

Applications · Statistics 2010-06-08 John Chakerian , Susan Holmes

Many inverse problems require reconstructing physical fields from limited and noisy data while incorporating known governing equations. A growing body of work within probabilistic numerics formalizes such tasks via Bayesian inference in…

Machine Learning · Statistics 2025-12-19 Alex Alberts , Ilias Bilionis

We study a generalization of the Brownian bridge as a stochastic process that models the position and velocity of inertial particles between the two end-points of a time interval. The particles experience random acceleration and are assumed…

Systems and Control · Computer Science 2014-07-15 Yongxin Chen , Tryphon Georgiou

We construct in this article a rough path over fractional Brownian motion with arbitrary Hurst index by (i) using the Fourier normal ordering algorithm introduced in \cite{Unt-Holder} to reduce the problem to that of regularizing tree…

Probability · Mathematics 2010-06-30 Jeremie Unterberger

The real trees form a class of metric spaces that extends the class of trees with edge lengths by allowing behavior such as infinite total edge length and vertices with infinite branching degree. We use Dirichlet form methods to construct…

Probability · Mathematics 2011-10-12 Siva Athreya , Michael Eckhoff , Anita Winter

We establish the discrete approximation to Brownian motion with varying dimension (BMVD in abbreviation) by random walks. The setting is very similar to that in [11], but here we use a different method allowing us to get rid the…

Probability · Mathematics 2021-11-16 Shuwen Lou

Ultrametric matrices are a class of covariance matrices that arise in latent tree models. As a parameter space in a statistical model, the set of ultrametric matrices is neither convex nor a smooth manifold. Focus in the literature has…

Methodology · Statistics 2025-04-28 Tsung-Hung Yao , Zhenke Wu , Karthik Bharath , Veerabhadran Baladandayuthapani
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