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We propose a general method to study dependent data in a binary tree, where an individual in one generation gives rise to two different offspring, one of type 0 and one of type 1, in the next generation. For any specific characteristic of…

Probability · Mathematics 2009-09-29 Julien Guyon

This paper provides a detailed analysis of the lower deviation probability properties for a $d$-type ($d>1$) Galton--Watson (GW) process $\{\textbf{Z}_n=(Z_n^{(i)})_{1\le i\le d};n\ge0\}$ in both Schr\"{o}der and B\"{o}ttcher cases. We…

Probability · Mathematics 2025-07-01 Tan Jiangrui

Tree-structured data naturally appear in various fields, particularly in biology where plants and blood vessels may be described by trees, but also in computer science because XML documents form a tree structure. This paper is devoted to…

Statistics Theory · Mathematics 2019-04-09 Romain Azaïs , Alexandre Genadot , Benoît Henry

We investigate the genealogical structure of general critical or subcritical continuous-state branching processes. Analogously to the coding of a discrete tree by its contour function, this genealogical structure is coded by a real-valued…

Probability · Mathematics 2007-05-23 Thomas Duquesne , Jean-Francois Le Gall

We present a new algorithm for computing the quasi-stationary distribution of subcritical Galton--Watson branching processes. This algorithm is based on a particular discretization of a well-known functional equation that characterizes the…

Numerical Analysis · Mathematics 2020-01-27 Sophie Hautphenne , Stefano Massei

For gauge theory, the matrix element for any physical process is independent of the gauge used. Since this is a formal statement and examples are known where gauge invariance is violated, for any specific process this gauge invariance needs…

High Energy Physics - Phenomenology · Physics 2018-12-10 Tai Tsun Wu , Sau Lan Wu

Doubly intractable distributions arise in many settings, for example in Markov models for point processes and exponential random graph models for networks. Bayesian inference for these models is challenging because they involve intractable…

Computation · Statistics 2019-04-03 Jaewoo Park , Murali Haran

Self-similar Markov trees constitute a remarkable family of random compact real trees carrying a decoration function that is positive on the skeleton. As the terminology suggests, they are self-similar objects that further satisfy a Markov…

Probability · Mathematics 2025-04-16 Jean Bertoin , Nicolas Curien , Armand Riera

The first aim of this paper is to introduce a class of Markov chains on $\mathbb{Z}_+$ which are discrete self-similar in the sense that their semigroups satisfy an invariance property expressed in terms of a discrete random dilation…

Probability · Mathematics 2022-03-08 Laurent Miclo , Pierre Patie , Rohan Sarkar

In this paper, we extend a previously developed recursive entropic segmentation scheme for applications to biological sequences. Instead of Bernoulli chains, we model the statistically stationary segments in a biological sequence as Markov…

Genomics · Quantitative Biology 2009-04-17 Siew-Ann Cheong , Paul Stodghill , David J. Schneider , Samuel W. Cartinhour , Christopher R. Myers

We give computable bounds on the rate of convergence of the transition probabilities to the stationary distribution for a certain class of geometrically ergodic Markov chains. Our results are different from earlier estimates of Meyn and…

Probability · Mathematics 2007-05-23 Peter H. Baxendale

We study two different versions of the simple exclusion process on augmented Galton-Watson trees, the constant speed model and the varying speed model. In both cases, the simple exclusion process starts from an equilibrium distribution with…

Probability · Mathematics 2020-07-07 Nina Gantert , Dominik Schmid

We provide explicit nonasymptotic estimates for the rate of convergence of empirical means of Markov chains, together with a Gaussian or exponential control on the deviations of empirical means. These estimates hold under a "positive…

Probability · Mathematics 2010-11-11 Aldéric Joulin , Yann Ollivier

Bayesian causal discovery aims to infer the posterior distribution over causal models from observed data, quantifying epistemic uncertainty and benefiting downstream tasks. However, computational challenges arise due to joint inference over…

Machine Learning · Computer Science 2023-12-11 Yashas Annadani , Nick Pawlowski , Joel Jennings , Stefan Bauer , Cheng Zhang , Wenbo Gong

Using changes of probability measure developed by \mbox{Grama} and Haeusler (Stochastic Process.\ Appl., 2000), we obtain two generalizations of the deviation inequalities of Lanzinger and Stadtm\"{u}ller (Stochastic Process.\ Appl., 2000)…

Probability · Mathematics 2017-08-03 Xiequan Fan

We study the large-deviation properties of minimum spanning trees for two ensembles of random graphs with $N$ nodes. First, we consider complete graphs. Second, we study Erd\H{o}s-R\'{e}nyi (ER) random graphs with edge probability $p=c/N$…

Disordered Systems and Neural Networks · Physics 2025-12-16 Mahdi Sarikhani , Alexander K. Hartmann

We consider a class of small-sample distribution estimators over noisy channels. Our estimators are designed for repetition channels, and rely on properties of the runs of the observed sequences. These runs are modeled via a special type of…

Information Theory · Computer Science 2012-02-07 Farzad Farnoud , Narayana P. Santhanam , Olgica Milenkovic

We consider the problem of estimating the differences between two causal directed acyclic graph (DAG) models with a shared topological order given i.i.d. samples from each model. This is of interest for example in genomics, where changes in…

Methodology · Statistics 2018-11-08 Yuhao Wang , Chandler Squires , Anastasiya Belyaeva , Caroline Uhler

We study a linear-fractional Bienaym\'e-Galton-Watson process with a general type space. The corresponding tree contour process is described by an alternating random walk with the downward jumps having a geometric distribution. This leads…

Probability · Mathematics 2016-03-07 Alexey Lindo , Serik Sagitov

In this paper, we present new Poisson-type deviation inequalities for continuous-time Markov chains whose Wasserstein curvature or $\Gamma$-curvature is bounded below. Although these two curvatures are equivalent for Brownian motion on…

Probability · Mathematics 2007-09-14 Aldéric Joulin
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