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We introduce a probabilistic framework for two-sample comparison based on a nonparametric process taking the form of a Markov model that transitions between a "divide" and a "merge" state on a multi-resolution partition tree of the sample…

Methodology · Statistics 2014-05-30 Jacopo Soriano , Li Ma

Potential theory is a central tool to understand and analyse Markov processes. In this article, we develop its probabilistic counterpart for branching Markov chains. Specifically, we examine versions of quasi-processes or interlacements…

Probability · Mathematics 2023-11-07 Steffen Dereich , Martin Maiwald

Our principal aim is to observe the Markov discrete-time process of population growth with long-living trajectory. First we study asymptotical decay of generating function of Galton-Watson process for all cases as the Basic Lemma.…

Probability · Mathematics 2020-04-21 Azam A. Imomov

We propose a new algorithm to do posterior sampling of Kingman's coalescent, based upon the Particle Markov Chain Monte Carlo methodology. Specifically, the algorithm is an instantiation of the Particle Gibbs Sampling method, which…

Machine Learning · Statistics 2013-05-07 Yifei Chen , Xiaohui Xie

It is possible to represent each of a number of Markov chains as an evolving sequence of connected subsets of a directed acyclic graph that grow in the following way: initially, all vertices of the graph are unoccupied, particles are fed in…

Probability · Mathematics 2015-03-17 Steven N. Evans , Rudolf Gruebel , Anton Wakolbinger

A continuous time mixed state branching process is constructed as the scaling limits of two-type Galton-Watson processes. The process can also be obtained by the pathwise unique solution to a stochastic equation system. From the stochastic…

Probability · Mathematics 2021-04-28 Shukai Chen , Zenghu Li

We consider the problem of estimating the elapsed time since the most recent common ancestor of a finite random sample drawn from a population which has evolved through a Bienayme-Galton-Watson branching process. More specifically, we are…

Populations and Evolution · Quantitative Biology 2019-09-04 Conrad J. Burden , Albert C. Soewongsono

We consider the exchangeable fragmentation-coagulation (EFC) processes, where the coagulations are multiple and not simultaneous, as in a $\Lambda$-coalescent, and the fragmentations dislocate at finite rate an individual block into…

Probability · Mathematics 2020-12-18 Clément Foucart , Xiaowen Zhou

In this paper, we investigate a stochastic model describing the time evolution of a polymerization process. A polymer is a macro-molecule resulting from the aggregation of several elementary sub-units called monomers. Polymers can grow by…

Probability · Mathematics 2018-08-24 Philippe Robert , Wen Sun

We consider a random model of diffusion and coagulation. A large number of small particles are randomly scattered at an initial time. Each particle has some integer mass and moves in a Brownian motion whose diffusion rate is determined by…

Probability · Mathematics 2012-08-21 Alan Hammond , Fraydoun Rezakhanlou

Let W be the number of points in (0,t] of a stationary finite-state Markov renewal point process. We derive a bound for the total variation distance between the distribution of W and a compound Poisson distribution. For any nonnegative…

Probability · Mathematics 2007-05-23 Torkel Erhardsson

We develop a coagulation-fragmentation model to study a system composed of a small number of stochastic objects moving in a confined domain, that can aggregate upon binding to form local clusters of arbitrary sizes. A cluster can also…

Subcellular Processes · Quantitative Biology 2012-01-19 Nathanael Hoze , David Holcman

A branching L\'evy process can be seen as the continuous-time version of a branching random walk. It describes a particle system on the real line in which particles move and reproduce independently in a Poissonian manner. Just as for L\'evy…

Probability · Mathematics 2019-05-21 Jean Bertoin , Bastien Mallein

The initial purpose of this work is to provide a probabilistic explanation of a recent result on a version of Smoluchowski's coagulation equations in which the number of aggregations is limited. The latter models the deterministic evolution…

Probability · Mathematics 2009-11-13 Jean Bertoin , Vladas Sidoravicius

Convergence diagnosis for Markov chain Monte Carlo is a matter of fundamental importance in computational statistics: it determines the resources allocated to a particular sampling problem and influences the practitioner's view of the…

Computation · Statistics 2026-05-14 Buu Phan , Gergely Flamich , Ashish Khisti , Shahab Asoodeh

The continuous time Markov process considered in this paper belongs to a class of population models with linear growth and catastrophes. There, the catastrophes happen at the arrival times of a Poisson process, and at each catastrophe time,…

Probability · Mathematics 2019-05-14 A. Logachov , O. Logachova , A. Yambartsev

The step-growth polymerisation of a mixture of arbitrary-functional monomers is viewed as a time-continuos random graph process with degree bounds that are not necessarily the same for different vertices. The sequence of degree bounds acts…

Combinatorics · Mathematics 2019-08-21 Ivan Kryven

We have studied Markov processes on denumerable state space and continuous time. We found that all these processes are connected via gauge transformations. We have used this result before as a method for resolution of equations, included…

Statistical Mechanics · Physics 2019-09-12 M. Caruso , C. Jarne

The coalescent is a stochastic process representing ancestral lineages in a population undergoing neutral genetic drift. Originally defined for a well-mixed population, the coalescent has been adapted in various ways to accommodate spatial,…

Populations and Evolution · Quantitative Biology 2024-07-02 Benjamin Allen , Alex McAvoy

We study the size of connected components of random nearest-neighbor graphs with vertex set the points of a homogeneous Poisson point process in ${\mathbb{R}}^d$. The connectivity function is shown to decay superexponentially, and we…

Probability · Mathematics 2007-05-23 Iva Kozakova , Ronald Meester , Seema Nanda