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For a one-locus haploid infinite population with discrete generations, the celebrated Kingman's model describes the evolution of fitness distributions under the competition of selection and mutation, with a constant mutation probability.…

Probability · Mathematics 2021-06-01 Linglong Yuan

In this article we survey properties of mixed Poisson distributions and probabilistic aspects of the Stirling transform: given a non-negative random variable $X$ with moment sequence $(\mu_s)_{s\in\mathbb{N}}$ we determine a discrete random…

Combinatorics · Mathematics 2014-09-12 Markus Kuba , Alois Panholzer

Recent advances in Bayesian models for random partitions have led to the formulation and exploration of Exchangeable Sequences of Clusters (ESC) models. Under ESC models, it is the cluster sizes that are exchangeable, rather than the…

Statistics Theory · Mathematics 2022-09-08 Keith Levin , Brenda Betancourt

We introduce a mean-field framework for the study of systems of interacting particles sharing a conserved quantity. The work generalises and unites the existing fields of asset-exchange models, often applied to socio-economic systems, and…

Physics and Society · Physics 2021-06-14 Dominic T Robson , Andreas CW Baas , Alessia Annibale

We establish convergence to the Kingman coalescent for the genealogy of a geographically - or otherwise - structured version of the Wright-Fisher population model with fast migration. The new feature is that migration probabilities may…

Probability · Mathematics 2010-06-25 Serik Sagitov , Peter Jagers , Vladimir Vatutin

Bertoin and Le Gall (2003) introduced a certain probability measure valued Markov process that describes the evolution of a population, such that a sample from this population would exhibit a genealogy given by the so-called…

Probability · Mathematics 2007-05-23 Andreas Nordvall Lagerås

Take a continuous-time Galton-Watson tree. If the system survives until a large time $T$, then choose $k$ particles uniformly from those alive. What does the ancestral tree drawn out by these $k$ particles look like? Some special cases are…

Probability · Mathematics 2019-02-14 Simon C. Harris , Samuel G. G. Johnston , Matthew I. Roberts

Cross-classified data frequently arise in scientific fields such as education, healthcare, and social sciences. A common modeling strategy is to introduce crossed random effects within a regression framework. However, this approach often…

Methodology · Statistics 2025-07-22 Shota Takeishi , Shonosuke Sugasawa

We first study crossing statistics in random connection models (RCM) built on marked Poisson point processes on $\mathbb R^d$. Under general assumptions, we show exponential tail bounds for the number of crossings of a box contained in the…

Probability · Mathematics 2025-10-29 Alessandra Faggionato , Ivailo Hartarsky

We investigate the infinitely many demes limit of the genealogy of a sample of individuals from a subdivided population subject to sporadic mass extinction events. By exploiting a separation of timescales property of Wright's island model,…

Probability · Mathematics 2009-01-29 Jesse E. Taylor , Amandine Veber

Begin continuous time random walks from every vertex of a graph and have particles coalesce when they collide. We use a duality relation with the voter model to prove the process is site recurrent on bounded degree graphs, and for…

Probability · Mathematics 2015-10-19 Itai Benjamini , Eric Foxall , Ori Gurel-Gurevich , Matthew Junge , Harry Kesten

We study the loop clusters induced by Poissonian ensembles of Markov loops on a finite or countable graph (Markov loops can be viewed as excursions of Markov chains with a random starting point, up to re-rooting). Poissonian ensembles are…

Probability · Mathematics 2013-04-17 Yves Le Jan , Sophie Lemaire

Linear structural equation models, which relate random variables via linear interdependencies and Gaussian noise, are a popular tool for modeling multivariate joint distributions. These models correspond to mixed graphs that include both…

Computation · Statistics 2015-04-14 Mathias Drton , Luca Weihs

We consider the task of modeling a dependent sequence of random partitions. It is well-known that a random measure in Bayesian nonparametrics induces a distribution over random partitions. The community has therefore assumed that the best…

Methodology · Statistics 2021-08-03 Garritt L. Page , Fernando A. Quintana , David B. Dahl

In this note, we present a novel connection between a multi-type (vector) multiplicative coalescent process and a multi-type branching process with Poisson offspring distributions. More specifically, we show that the equations that govern…

Probability · Mathematics 2025-10-28 Heshan Aravinda , Yevgeniy Kovchegov , Peter T. Otto , Amites Sarkar

Partition-wise models offer a flexible approach for modeling complex and multidimensional data that are capable of producing interpretable results. They are based on partitioning the observed data into regions, each of which is modeled with…

Methodology · Statistics 2017-06-07 Rex C. Y. Cheung , Alexander Aue , Thomas C. M. Lee

In this paper the generalization of the Poisson distribution is derived for the case when each consecutive event changes event rate. A simple formula for the probability of observing of a given number of events for the selected period of…

Data Analysis, Statistics and Probability · Physics 2014-01-06 E. A. Kushnirenko

In this paper we consider a random partition of the plane into cells, the partition being based on the nodes and links of a {\it random planar geometric graph}. The resulting structure generalises the \emph{random \tes}\ hitherto studied in…

Probability · Mathematics 2016-06-07 Richard Cowan , Albert K. L. Tsang

Identification of local structure in intensive data -- such as time series, images, and higher dimensional processes -- is an important problem in astronomy. Since the data are typically generated by an inhomogeneous Poisson process, an…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Jeffrey D. Scargle

Random point patterns are ubiquitous in nature, and statistical models such as point processes, i.e., algorithms that generate stochastic collections of points, are commonly used to simulate and interpret them. We propose an application of…

Quantum Physics · Physics 2020-03-04 Soran Jahangiri , Juan Miguel Arrazola , Nicolás Quesada , Nathan Killoran
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