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Binary trait data record the presence or absence of distinguishing traits in individuals. We treat the problem of estimating ancestral trees with time depth from binary trait data. Simple analysis of such data is problematic. Each homology…

Methodology · Statistics 2009-08-31 Geoff K. Nicholls , Russell D. Gray

We study the local limit of the fixed-point forest, a tree structure associated to a simple sorting algorithm on permutations. This local limit can be viewed as an infinite random tree that can be constructed from a Poisson point process…

Probability · Mathematics 2023-06-22 Samuel Regan , Erik Slivken

We study fragmentation of a random recursive tree into a forest by repeated removal of nodes. The initial tree consists of N nodes and it is generated by sequential addition of nodes with each new node attaching to a randomly-selected…

Statistical Mechanics · Physics 2014-12-25 Z. Kalay , E. Ben-Naim

A power law degree distribution is established for a graph evolution model based on the graph class of k-trees. This k-tree-based graph process can be viewed as an idealized model that captures some characteristics of the preferential…

Discrete Mathematics · Computer Science 2008-11-27 Yong Gao

We consider a preferential attachment model that incorporates an anomaly. Our goal is to understand the evolution of the network before and after the occurrence of the anomaly by studying the influence of the anomaly on the structural…

Physics and Society · Physics 2025-05-07 Qiu Liang , Remco van der Hofstad , Nelly Litvak

Tree-based priors for probability distributions are usually specified using a predetermined, data-independent collection of candidate recursive partitions of the sample space. To characterize an unknown target density in detail over the…

Methodology · Statistics 2025-04-14 Li Ma , Benedetta Bruni

Random forests have become an established tool for classification and regression, in particular in high-dimensional settings and in the presence of complex predictor-response relationships. For bounded outcome variables restricted to the…

Methodology · Statistics 2019-01-21 Leonie Weinhold , Matthias Schmid , Marvin N. Wright , Moritz Berger

Paper proposes a model of large networks based on a random preferential attachment graph with addition of complete subgraphs (cliques). The proposed model refers to models of random graphs following the nonlinear preferential attachment…

Social and Information Networks · Computer Science 2019-04-05 E. B. Yudin

We consider linear preferential attachment trees, and show that they can be regarded as random split trees in the sense of Devroye (1999), although with infinite potential branching. In particular, this applies to the random recursive tree…

Probability · Mathematics 2017-06-20 Svante Janson

We introduce a new model of correlated randomly growing graphs and study the fundamental questions of detecting correlation and estimating aspects of the correlated structure. The model is simple and starts with any model of randomly…

Probability · Mathematics 2020-04-29 Miklos Z. Racz , Anirudh Sridhar

The "power of choice" has been shown to radically alter the behavior of a number of randomized algorithms. Here we explore the effects of choice on models of tree and network growth. In our models each new node has k randomly chosen…

Statistical Mechanics · Physics 2009-11-13 Raissa M. D'Souza , Paul L. Krapivsky , Cristopher Moore

Sum-Product Networks with complex probability distribution at the leaves have been shown to be powerful tractable-inference probabilistic models. However, while learning the internal parameters has been amply studied, learning complex leaf…

Machine Learning · Computer Science 2017-06-15 Mattia Desana , Christoph Schnörr

Binary trees are fundamental objects in models of evolutionary biology and population genetics. Here, we discuss some of their combinatorial and structural properties as they depend on the tree class considered. Furthermore, the process by…

Populations and Evolution · Quantitative Biology 2021-06-30 Thomas Wiehe

The aim of this paper is to develop a method for proving almost sure convergence in Gromov-Hausodorff-Prokhorov topology for a class of models of growing random graphs that generalises R\'emy's algorithm for binary trees. We describe the…

Probability · Mathematics 2020-02-25 Delphin Sénizergues

An electrical network with the structure of a random tree is considered: starting from a root vertex, in one iteration each leaf (a vertex with zero or one adjacent edges) of the tree is extended by either a single edge with probability $p$…

Statistical Mechanics · Physics 2013-09-25 Ewan Colman , Geoff Rodgers

Tree-based ensemble methods such as random forests, gradient-boosted trees, and Bayesianadditive regression trees have been successfully used for regression problems in many applicationsand research studies. In this paper, we study ensemble…

Machine Learning · Statistics 2024-06-21 Alexandre Seiller , Éric Gaussier , Emilie Devijver , Marianne Clausel , Sami Alkhoury

In this paper, we provide a polynomial time algorithm to calculate the probability of a {\it ranked} gene tree topology for a given species tree, where a ranked tree topology is a tree topology with the internal vertices being ordered. The…

Populations and Evolution · Quantitative Biology 2012-03-02 Tanja Stadler , James H. Degnan

A tanglegram consists of two binary rooted trees with the same number of leaves and a perfect matching between the leaves of the trees. We show that the two halves of a random tanglegram essentially look like two independently chosen random…

Combinatorics · Mathematics 2016-04-08 Matjaž Konvalinka , Stephan Wagner

We study a new class of preferential attachment trees with \emph{self-reinforcement}. At each time, each vertex is assigned a weight equal to the cumulative sum over past times of an affine function of its degree. A new vertex attaches…

Probability · Mathematics 2026-05-21 Shankar Bhamidi , Remco van der Hofstad , Frank den Hollander , Rounak Ray

We consider random walks that start and are absorbed on the leaves of random networks and study the length of such walks. For the networks we investigate, Erdos-Renyi random graphs and Barabasi-Albert scale free networks, these walks are…

Disordered Systems and Neural Networks · Physics 2016-07-11 David Lancaster
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