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In this paper, we study the Galton-Watson process in the random environment for the particular case when the number of the offsprings in each generation has the fractional linear generation function with random parameters. In this case, the…

Probability · Mathematics 2020-12-01 Dan Han , Stanislav Molchanov , Yanjmaa Jutmaan

A Galton-Watson process in varying environment is a discrete time branching process where the offspring distributions vary among generations. Based on a two-spine decomposition technique, we provide a probabilistic argument of a Yaglom-type…

Probability · Mathematics 2020-10-16 Natalia Cardona-Tobón , Sandra Palau

We establish a general sufficient condition for a sequence of Galton Watson branching processes in varying environment to converge weakly. This condition extends previous results by allowing offspring distributions to have infinite…

Probability · Mathematics 2014-09-22 Vincent Bansaye , Florian Simatos

We define a model of Galton Watson processes in dynamical environments where the environment evolves according to a dynamical system (X, T). Three behaviours are possible: uniformly subcritical, critical, and uniformly supercritical. We…

Dynamical Systems · Mathematics 2024-10-28 Thomas Morand

Branching processes in a varying environment encompass a wide range of stochastic demographic models, and their complete understanding in terms of limit behaviour poses a formidable research challenge. In this paper, we conduct a thorough…

Probability · Mathematics 2025-11-18 Serik Sagitov , Alexey Lindo , Yerakhmet Zhumayev

This paper deals with branching processes in varying environment, namely, whose offspring distributions depend on the generations. We provide sufficient conditions for survival or extinction which rely only on the first and second moments…

Probability · Mathematics 2017-09-29 Daniela Bertacchi , Pablo M. Rodriguez , Fabio Zucca

We prove a scaling limit theorem for discrete Galton-Watson processes in varying environments. A simple sufficient condition for the weak convergence in the Skorokhod space is given in terms of probability generating functions. The limit…

Probability · Mathematics 2022-04-14 Fang Rongjuan , Li Zenghu , Liu Jiawei

We study an extension of the so-called defective Galton-Watson processes obtained by allowing the offspring distribution to change over the generations. Thus, in these processes, the individuals reproduce independently of the others and in…

Probability · Mathematics 2021-10-01 Götz Kersting , Carmen Minuesa

A Galton-Watson process in a varying environment is a discrete time branching process where the offspring distributions vary among generations. It is known that in the critical case, these processes have a Yaglom limit, that is, a suitable…

Probability · Mathematics 2024-10-03 Natalia Cardona-Tobón , Arturo Jaramillo , Sandra Palau

Branching processes $(Z_n)_{n \ge 0}$ in a varying environment generalize the Galton-Watson process, in that they allow time-dependence of the offspring distribution. Our main results concern general criteria for a.s. extinction,…

Probability · Mathematics 2019-11-11 Götz Kersting

The linear-fractional Galton-Watson processes is a well known case when many characteristics of a branching process can be computed explicitly. In this paper we extend the two-parameter linear-fractional family to a much richer…

Probability · Mathematics 2015-12-11 Serik Sagitov , Alexey Lindo

This paper is concerned with an extended Galton-Watson process so as to allow individuals to live and reproduce for more than one unit time. We assume that each individual can live $k$ seasons (time-units) with probability $h_k$, and…

Probability · Mathematics 2022-03-29 J. R. Tan , J. P. Li

A branching process in random environment $(Z_n, n \in \N)$ is a generalization of Galton Watson processes where at each generation the reproduction law is picked randomly. In this paper we give several results which belong to the class of…

Probability · Mathematics 2008-12-15 Vincent Bansaye , Julien Berestycki

We give sufficient conditions on the offspring, the initial and the immigration distributions under which a second-order Galton-Watson process with immigration is regularly varying.

Probability · Mathematics 2018-05-03 Zsuzsanna Bősze , Gyula Pap

Conditioning a multitype Galton-Watson process to stay alive into the indefinite future leads to what is known as its associated $Q$-process. We show that the same holds true if the process is conditioned to reach a positive threshold or a…

Probability · Mathematics 2016-03-09 Sophie Pénisson

We consider an indecomposable Galton-Watson branching process with countably infinitely many types. Assuming that the process is critical and allowing for infinite variance of the offspring sizes of some (or all) types of particles we…

Probability · Mathematics 2020-03-02 V. A. Topchii , V. A. Vatutin , E. E. Dyakonova

The Galton-Watson process is a Markov chain modeling the population size of independently reproducing particles giving birth to $k$ offspring with probability $p_k$, $k\ge0$. In this paper we consider {\it defective} Galton-Watson processes…

Probability · Mathematics 2016-12-13 Serik Sagitov , Carmen Minuesa

A properly scaled critical Galton-Watson process converges to a continuous state critical branching process $\xi(\cdot)$ as the number of initial individuals tends to infinity. We extend this classical result by allowing for overlapping…

Probability · Mathematics 2021-08-10 Serik Sagitov

We give sufficient conditions on the initial, offspring and immigration distributions under which the distribution of a not necessarily stationary Galton--Watson process with immigration is regularly varying at any fixed time.

Probability · Mathematics 2018-06-08 Matyas Barczy , Zsuzsanna Bősze , Gyula Pap

We consider a multitype Galton-Watson process that allows for the mutation and reversion of individual types in discrete and continuous time. In this setting, we explicitly compute the time evolution of quantities such as the mean and…

Populations and Evolution · Quantitative Biology 2026-01-01 Qiao Huang , Nicolas Privault
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