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Phylogenetics uses alignments of molecular sequence data to learn about evolutionary trees. Substitutions in sequences are modelled through a continuous-time Markov process, characterised by an instantaneous rate matrix, which standard…

Populations and Evolution · Quantitative Biology 2020-07-20 Naomi E. Hannaford , Sarah E. Heaps , Tom M. W. Nye , Tom A. Williams , T. Martin Embley

We study age-structured branching models with reproduction law depending on the remaining lifetime of the parent. The lifespan of an individual is decided at its birth and its remaining lifetime decreases at the unit speed. The models…

Probability · Mathematics 2024-01-08 Ziling Cheng , Zenghu Li

Historically, matrix projection models (MPMs) have been employed to study population dynamics with regard to size, age or structure. To work with continuous traits, in the past decade, integral projection models (IPMs) have been proposed.…

Methodology · Statistics 2013-12-30 Alan E. Gelfand , Souparno Ghosh , James S. Clark

Mast fruiting represents a synchronous population behaviour which can spread on large landscape areas. This reproductive pattern is generally perceived as a synchronous periodic production of large seed crops and has a significant practical…

Quantitative Methods · Quantitative Biology 2016-02-12 Ciprian Palaghianu , Marian Dragoi

We survey results on the description of stochastically evolving genealogies of populations and marked genealogies of multitype populations or spatial populations via tree-valued Markov processes on (marked) ultrametric measure spaces. In…

Probability · Mathematics 2018-09-21 Andrej Depperschmidt , Andreas Greven

We consider the problem of bounding mean first passage times for a class of continuous-time Markov chains that captures stochastic interactions between groups of identical agents. The quantitative analysis of such probabilistic population…

Systems and Control · Electrical Eng. & Systems 2020-04-07 Michael Backenköhler , Luca Bortolussi , Verena Wolf

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

We are interested in modelling Darwinian evolution, resulting from the interplay of phenotypic variation and natural selection through ecological interactions. Our models are rooted in the microscopic, stochastic description of a population…

Probability · Mathematics 2016-08-16 Nicolas Champagnat , Régis Ferrière , Sylvie Méléard

We propose a general method to study dependent data in a binary tree, where an individual in one generation gives rise to two different offspring, one of type 0 and one of type 1, in the next generation. For any specific characteristic of…

Probability · Mathematics 2009-09-29 Julien Guyon

Branching processes are a class of continuous-time Markov chains (CTMCs) prevalent for modeling stochastic population dynamics in ecology, biology, epidemiology, and many other fields. The transient or finite-time behavior of these systems…

Computation · Statistics 2023-02-24 Achal Awasthi , Jason Xu

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 an asexually reproducing population on a finite type space whose evolution is driven by exponential birth, death and competition rates, as well as the possibility of mutation at a birth event. On the individual-based level this…

Populations and Evolution · Quantitative Biology 2020-02-10 Anna Kraut , Anton Bovier

We consider a stochastic individual based model where each predator searches during a random time and then manipulates its prey or rests. The time distributions may be non-exponential. An age structure allows to describe these interactions…

Dynamical Systems · Mathematics 2021-03-31 Vincent Bansaye , Bertand Cloez

We study memory dependent binary-state dynamics, focusing on the noisy-voter model. This is a non-Markovian process if we consider the set of binary states of the population as the description variables, or Markovian if we incorporate…

Physics and Society · Physics 2020-02-25 Antonio F. Peralta , Nagi Khalil , Raul Toral

In proliferating cell populations, adaptive changes to biochemical reactions can change a cell's division time, which in turn can change the population size. However, biochemical reactions are subject to noise, and therefore the conditions…

Biological Physics · Physics 2026-05-06 Krishna P. Ramachandran , Motasem ElGamel , Farshid Jafarpour , Andrew Mugler

The Batch Markov Modulated Poisson Process (BMMPP) is a subclass of the versatile Batch Markovian Arrival process (BMAP) which has been proposed for the modeling of dependent events occurring in batches (as group arrivals, failures or risk…

Computation · Statistics 2024-01-29 Yoel G. Yera , Rosa E. Lillo , Pepa Ramírez-Cobo

(Multi-type) branching processes are a natural and well-studied model for generating random infinite trees. Branching processes feature both nondeterministic and probabilistic branching, generalizing both transition systems and Markov…

Logic in Computer Science · Computer Science 2021-07-06 Stefan Kiefer , Pavel Semukhin , Cas Widdershoven

The purpose of this paper is to study a Markovian metapopulation model on a directed graph with edge-supported transfers and deterministic intra-nodal population dynamics. We first state tractable stability conditions for two typical…

Probability · Mathematics 2019-05-28 Pierre Montagnon

The growth of a population is often modeled as branching process where each individual at the end of its life is replaced by a certain number of offspring. An example of these branching models is the Bellman-Harris process, where the…

We provide a probabilistic approach to modeling the movements of subjects through multiple stages, with "stays" or survival at each stage for a random length of time, and ending at a desired final stage. We use conditional Markov chains…

Methodology · Statistics 2018-01-16 Martial Longla , Siva Sivaganesan