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Related papers: On population growth with catastrophes

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We consider a stochastic population model where the intrinsic or demographic noise causes cycling between states before the population eventually goes extinct. A master equation approach coupled with a WKB (Wentzel-Kramers-Brillouin)…

Populations and Evolution · Quantitative Biology 2014-12-16 Garrett Nieddu , Lora Billings , Eric Forgoston

In this paper we consider a control problem for a Partially Observable Piecewise Deterministic Markov Process of the following type: After the jump of the process the controller receives a noisy signal about the state and the aim is to…

Optimization and Control · Mathematics 2021-07-21 Nicole Bäuerle , Dirk Lange

In this article we study the long time behaviour of measure-valued birth and death processes in continuous time, where the dynamics between jumps are one-dimensional Markov processes including diffusion and jumps. We consider the three…

Probability · Mathematics 2025-08-07 Pierre Collet , Sylvie Méléard , Jaime San

We consider a Markov jump process on a general state space to which we apply a time-dependent weak perturbation over a finite time interval. By martingale-based stochastic calculus, under a suitable exponential moment bound for the…

Probability · Mathematics 2024-05-14 Alessandra Faggionato , Vittoria Silvestri

Stochastic gene regulatory networks with bursting dynamics can be modeled mesocopically as a generalized density-dependent Markov chain (GDDMC) or macroscopically as a piecewise-deterministic Markov process (PDMP). Here we prove a limit…

Probability · Mathematics 2019-09-04 Xian Chen , Chen Jia

We study a generalised model of population growth in which the state variable is population growth rate instead of population size. Stochastic parametric perturbations, modelling phenotypic variability, lead to a Langevin system with two…

Populations and Evolution · Quantitative Biology 2010-10-15 Harold P. de Vladar , Ido Pen

It has been shown by Bertoin and Yor (2002) that the law of positive self-similar Markov processes (pssMps) that only jump downwards and do not hit zero in finite time are uniquely determined by their entire moments for which explicit…

Probability · Mathematics 2014-03-25 Matyas Barczy , Leif Doering

In this paper, we study the asymptotic of exit problem for controlled Markov diffusion processes with random jumps and vanishing diffusion terms, where the random jumps are introduced in order to modify the evolution of the controlled…

Dynamical Systems · Mathematics 2018-02-08 Getachew K. Befekadu

The purpose of this paper is to ensure the conditions of G\"artner-Ellis Theorem for evaluations of the empirical measure. We show that up-to-date conditions for ensuring the convergence to a quasi-stationary distribution can be applied…

Probability · Mathematics 2020-04-21 Aurélien Velleret

We investigate how a catastrophic event (modeled as a temporary fall of the reproduction rate) increases the extinction probability of an isolated self-regulated stochastic population. Using a variant of the Verhulst logistic model as an…

Populations and Evolution · Quantitative Biology 2014-08-06 Michael Assaf , Alex Kamenev , Baruch Meerson

We study the computational complexity of central analysis problems for One-Counter Markov Decision Processes (OC-MDPs), a class of finitely-presented, countable-state MDPs. OC-MDPs are equivalent to a controlled extension of (discrete-time)…

Computer Science and Game Theory · Computer Science 2009-09-11 Tomáš Brázdil , Václav Brožek , Kousha Etessami , Antonín Kučera , Dominik Wojtczak

We analyze the long-term stability of a stochastic model designed to illustrate the adaptation of a population to variation in its environment. A piecewise-deterministic process modeling adaptation is coupled to a Feller logistic diffusion…

Probability · Mathematics 2021-09-14 Aurélien Velleret

There has been substantial interest in developing Markov chain Monte Carlo algorithms based on piecewise-deterministic Markov processes. However existing algorithms can only be used if the target distribution of interest is differentiable…

Statistics Theory · Mathematics 2021-11-12 Augustin Chevallier , Sam Power , Andi Q. Wang , Paul Fearnhead

Piecewise deterministic Markov processes (PDMPs) are a type of continuous-time Markov process that combine deterministic flows with jumps. Recently, PDMPs have garnered attention within the Monte Carlo community as a potential alternative…

Methodology · Statistics 2024-10-23 Joris Bierkens , Kengo Kamatani , Gareth O. Roberts

The paper studies a class of critical Markov branching processes with infinite variance of the offspring distribution. The processes admit also an immigration component at the jump-points of a non-homogeneous Poisson process, assuming that…

Probability · Mathematics 2025-01-07 Kosto V. Mitov , Nikolay M. Yanev

Consider a discrete time Markov process $X^\epsilon$ on $\mathbf R^d$ that makes a deterministic jump based on its current location, and then takes a small Gaussian step of variance $\epsilon^2$. We study the behavior of the asymptotic…

Probability · Mathematics 2025-12-19 William Cooperman , Gautam Iyer , James Nolen

Consider a population where individuals give birth at constant rate during their lifetimes to i.i.d. copies of themselves. Individuals bear clonally inherited types, but (neutral) mutations may happen at the birth events. The smallest…

Probability · Mathematics 2013-05-29 Cécile Delaporte

We reconsider the deterministic haploid mutation-selection equation with two types. This is an ordinary differential equation that describes the type distribution (forward in time) in a population of infinite size. This paper establishes…

Probability · Mathematics 2020-09-25 Ellen Baake , Fernando Cordero , Sebastian Hummel

The present paper is devoted to the study of the long term dynamics of diffusion processes modelling a single species that experiences both demographic and environmental stochasticity. In our setting, the long term dynamics of the diffusion…

Probability · Mathematics 2024-07-10 Alexandru Hening , Weiwei Qi , Zhongwei Shen , Yingfei Yi

In this paper, we propose a novel class of Piecewise Deterministic Markov Processes (PDMPs) that are designed to sample from probability distributions $\pi$ supported on a convex set $\mathcal{M}$. This class of PDMPs adapts the concept of…

Computation · Statistics 2026-05-01 Joël Tatang Demano , Paul Dobson , Konstantinos Zygalakis
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