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Related papers: Reduced branching processes with very heavy tails

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This paper investigates tail asymptotics of stationary distributions and quasi-stationary distributions (QSDs) of continuous-time Markov chains on subsets of the non-negative integers. Based on the so-called flux-balance equation, we…

Probability · Mathematics 2023-08-16 Chuang Xu , Mads Christian Hansen , Carsten Wiuf

We give new formulas on the total number of born particles in the stable birth-and-assassination process, and prove that it has an heavy-tailed distribution. We also establish that this process is a scaling limit of a process of rumor…

Probability · Mathematics 2008-10-20 Charles Bordenave

We consider the evolution of populations under the joint action of mutation and differential reproduction, or selection. The population is modelled as a finite-type Markov branching process in continuous time, and the associated…

Populations and Evolution · Quantitative Biology 2009-02-23 Ellen Baake , Hans-Otto Georgii

We consider a Markov modulated fluid network with a finite number of stations. We are interested in the tail asymptotics behavior of the stationary distribution of its buffer content process. Using two different approaches, we derive upper…

Probability · Mathematics 2020-09-29 Masakiyo Miyazawa

Birth and death Markov processes can model stochastic physical systems from percolation to disease spread and, in particular, wildfires. We introduce and analyze a birth-death-suppression Markov process as a model of controlled culling of…

Adaptation and Self-Organizing Systems · Physics 2023-10-11 George Hulsey , David L. Alderson , Jean Carlson

In the present paper, we characterize the behavior of supercritical branching processes in random environment with linear fractional offspring distributions, conditioned on having small, but positive values at some large generation. As it…

Probability · Mathematics 2014-05-20 Christian Böinghoff

We define a multi-type coalescent point process of a general branching process with finitely many types. This multi-type coalescent fully describes the genealogy of the (quasi-stationary) standing population, providing types along ancestral…

Probability · Mathematics 2013-09-18 Lea Popovic , Mariolys Rivas

Heavy-tailed distributions are frequently used to enhance the robustness of regression and classification methods to outliers in output space. Often, however, we are confronted with "outliers" in input space, which are isolated observations…

Machine Learning · Statistics 2010-06-24 Fabian L. Wauthier , Michael I. Jordan

A simplified model for the growth of a population is studied in which random effects arise because reproducing individuals have a certain probability of surviving until the next breeding season and hence contributing to the next generation.…

Populations and Evolution · Quantitative Biology 2016-04-05 Henry C. Tuckwell

A multitype continuous-state branching process (MCSBP) ${\rm Z}=({\rm Z}_{t})_{t\geq 0}$, is a Markov process with values in $[0,\infty)^{d}$ that satisfies the branching property. Its distribution is characterised by its branching…

Probability · Mathematics 2021-09-08 Loïc Chaumont , Marine Marolleau

Reinforced processes are known to provide a stochastic representation for the quasi-stationary distribution of a given killed Markov process - describing the killed Markov process at fixed time instants. In this paper we shall adapt the…

Probability · Mathematics 2022-02-10 Oliver Tough

We derive the asymptotic behaviour of the genealogy of a logistic branching process in the setting where the equilibrium population size is large. In three regimes on the tail of the offspring distribution we recover the Kingman,…

Probability · Mathematics 2025-11-11 Ruairi Garrett , Julio Ernesto Nava Trejo

This paper demonstrates a new regeneration processes technology making use of positive stable distributions. We study the asymptotic behavior of branching processes with a randomly controlled migration component. Using the new method, we…

Probability · Mathematics 2007-05-23 George P. Yanev , Kosto V. Mitov , Nickolay M. Yanev

We provide a many-to-few formula in the general setting of non-local branching Markov processes. This formula allows one to compute expectations of k-fold sums over functions of the population at k different times. The result generalises…

Probability · Mathematics 2022-11-17 Simon C. Harris , Emma Horton , Ellen Powell , Andreas E. Kyprianou

We consider the tail distribution of the edge cover time of a specific non-Markov process, $\delta$ once-reinforced random walk, on finite connected graphs, whose transition probability is proportional to weights of edges. Here the weights…

Probability · Mathematics 2025-05-09 Xiangyu Huang , Yong Liu , Kainan Xiang

We consider the behaviour of branching-selection particle systems in the large population limit. The dynamics of these systems is the combination of the following three components: (a) Motion: particles move on the real line according to a…

Probability · Mathematics 2023-11-22 Jean Bérard , Brieuc Frénais

We derive the first conditionally consistent estimators for a class of parametric Markov population models with logistic growth, which are suitable for modelling endangered populations in restricted habitats with a carrying capacity. We…

Statistics Theory · Mathematics 2024-12-05 Peter Braunsteins , Sophie Hautphenne , Carmen Minuesa

We present a Markov-chain analysis of blockwise-stochastic algorithms for solving partially block-separable optimization problems. Our main contributions to the extensive literature on these methods are statements about the Markov operators…

Optimization and Control · Mathematics 2023-11-01 D. Russell Luke

Building on the spinal decomposition technique in Foutel-Rodier and Schertzer (2022) we prove a Yaglom limit law for the rescaled size of a nearly critical branching process in varying environment conditional on survival. In addition, our…

Probability · Mathematics 2025-09-30 Florin Boenkost , Félix Foutel-Rodier , Emmanuel Schertzer

We study the long time behaviour of a Markov process evolving in $\mathbb{N}$ and conditioned not to hit 0. Assuming that the process comes back quickly from infinity, we prove that the process admits a unique quasi-stationary distribution…

Probability · Mathematics 2013-04-04 Servet Martinez , Jaime San Martin , Denis Villemonais