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We are interested in the dynamic of a structured branching population where the trait of each individual moves according to a Markov process. The rate of division of each individual is a function of its trait and when a branching event…

Probability · Mathematics 2019-03-29 Aline Marguet

We study a density-dependent Markov jump process describing a population where each individual is characterized by a type, and reproduces at rates depending both on its type and on the population type distribution. We are interested in the…

Probability · Mathematics 2026-02-26 Madeleine Kubasch

We consider Markov jump processes describing structured populations with interactions via density dependance. We propose a Markov construction with a distinguished individual which allows to describe the random tree and random sample at a…

Probability · Mathematics 2022-07-20 Vincent Bansaye

We model the growth of a cell population using a piecewise deterministic Markov branching tree. In this model, each cell splits into two offspring at a division rate $B(x)$, which depends on its size $x$. The size of each cell increases…

Probability · Mathematics 2024-09-06 Nathalie Krell

In this work we model the dynamics of a population that evolves as a continuous time branching process with a trait structure and ecological interactions in form of mutations and competition between individuals. We generalize existing…

Probability · Mathematics 2020-10-19 Gabriel Berzunza , Anja Sturm , Anita Winter

We consider a branching model in discrete time where each individual has a trait in some general state space. Both the reproduction law and the trait inherited by the offsprings may depend on the trait of the mother and the environment. We…

Probability · Mathematics 2013-11-26 Vincent Bansaye

Motivated by the study of a parasite infection in a cell line, we introduce a general class of Markov processes for the modelling of population dynamics. The population process evolves as a diffusion with positive jumps whose rate is a…

Probability · Mathematics 2021-06-01 Aline Marguet , Charline Smadi

Density dependent Markov population processes with countably many types can often be well approximated over finite time intervals by the solution of the differential equations that describe their average drift, provided that the total…

Probability · Mathematics 2014-06-05 A. D. Barbour , Malwina Luczak

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 study the evolution of a particle system whose genealogy is given by a supercritical continuous time Galton--Watson tree. The particles move independently according to a Markov process and when a branching event occurs, the offspring…

Probability · Mathematics 2012-02-20 Vincent Bansaye , Jean-François Delmas , Laurence Marsalle , Viet Chi Tran

The first chapter concerns monotype population models. We first study general birth and death processes and we give non-explosion and extinction criteria, moment computations and a pathwise representation. We then show how different scales…

Probability · Mathematics 2017-07-06 Vincent Bansaye , Sylvie Méléard

A discrete time branching process where the offspring distribution is generation-dependent, and the number of reproductive individuals is controlled by a random mechanism is considered. This model is a Markov chain but, in general, the…

Probability · Mathematics 2024-01-30 Miguel González , Carmen Minuesa , Manuel Mota , Inés del Puerto , Alfonso Ramos

When modelling metapopulation dynamics, the influence of a single patch on the metapopulation depends on the number of individuals in the patch. Since the population size has no natural upper limit, this leads to systems in which there are…

Probability · Mathematics 2011-04-01 A. D. Barbour , M. J. Luczak

We consider a particle system in continuous time, discrete population, with spatial motion and nonlocal branching. The offspring's weights and their number may depend on the mother's weight. Our setting captures, for instance, the processes…

Probability · Mathematics 2012-10-12 Bertrand Cloez

We consider a class of density-dependent branching processes which generalises exponential, logistic and Gompertz growth. A population begins with a single individual, grows exponentially initially, and then growth may slow down as the…

Probability · Mathematics 2022-04-11 David Cheek

We consider a population with non-overlapping generations, whose size goes to infinity. It is described by a discrete genealogy which may be time non-homogeneous and we pay special attention to branching trees in varying environments. A…

Probability · Mathematics 2013-05-22 Vincent Bansaye , Chunmao Huang

We consider a broad class of continuous-time two-type population size-dependent Markov Branching Processes. The offspring distribution can depend on the current (alive) and total (dead and alive) populations. Using stochastic approximation…

Probability · Mathematics 2023-04-04 Khushboo Agarwal , Veeraruna Kavitha

A branching process in a Markovian environment consists of an irreducible Markov chain on a set of "environments" together with an offspring distribution for each environment. At each time step the chain transitions to a new random…

Probability · Mathematics 2021-06-22 Lila Greco , Lionel Levine

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

We are interested in the study of models describing the evolution of a polymorphic population with mutation and selection in the specific scales of the biological framework of adaptive dynamics. The population size is assumed to be large…

Probability · Mathematics 2011-12-05 Nicolas Champagnat , Sylvie Méléard
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