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We present a progress report for studies on maxima related to offspring in branching processes. We summarize and discuss the findings on the subject that appeared in the last ten years. Some of the results are refined and illustrated with…

Probability · Mathematics 2007-05-23 George P. Yanev

We introduce Generator Matching, a modality-agnostic framework for generative modeling using arbitrary Markov processes. Generators characterize the infinitesimal evolution of a Markov process, which we leverage for generative modeling in a…

Machine Learning · Computer Science 2025-02-28 Peter Holderrieth , Marton Havasi , Jason Yim , Neta Shaul , Itai Gat , Tommi Jaakkola , Brian Karrer , Ricky T. Q. Chen , Yaron Lipman

We investigate the application of the Adaptive Multilevel Splitting algorithm for the estimation of tail probabilities of solutions of Stochastic Differential Equations evaluated at a given time, and of associated temporal averages. We…

Probability · Mathematics 2019-03-27 Charles-Edouard Bréhier , Tony Lelièvre

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

We give Hoeffding and Bernstein-type concentration inequalities for the largest eigenvalue of sums of random matrices arising from a Markov chain. We consider time-dependent matrix-valued functions on a general state space, generalizing…

Probability · Mathematics 2025-07-01 Joe Neeman , Bobby Shi , Rachel Ward

Consider a sequence of Markov processes $X^1, X^2,...$ with state space $E$, where $X^N$ has a strong drift to $D \subseteq E$, such that $\Phi(X^N)$ is slow for some appropriate $\Phi: E\to D$. Using the method of martingale problems, we…

Probability · Mathematics 2026-02-19 Samuel Ayomide Adeosun , Peter Pfaffelhuber

This paper presents precise large deviation estimates for solutions to stochastic fixed point equations of the type V =_d f(V), where f(v) = Av + g(v) for a random function g(v) = o(v) a.s. as v tends to infinity. Specifically, we provide…

Probability · Mathematics 2011-03-15 Jeffrey F. Collamore , Anand N. Vidyashankar

We consider branching processes describing structured, interacting populations in continuous time. Dynamics of each individuals characteristics and branching properties can be influenced by the entire population. We propose a Girsanov-type…

Probability · Mathematics 2024-05-15 Charles Medous

Empirical processes for stationary, causal sequences are considered. We establish empirical central limit theorems for classes of indicators of left half lines, absolutely continuous functions and piecewise differentiable functions. Sample…

Statistics Theory · Mathematics 2007-06-13 Wei Biao Wu

Our motivation comes from the large population approximation of individual based models in population dynamics and population genetics. We propose a general method to investigate scaling limits of finite dimensional population size Markov…

Probability · Mathematics 2018-11-07 Vincent Bansaye , Maria-Emilia Caballero , Sylvie Méléard

Consider a Lamperti-Kiu Markov additive process $(J_t,\xi_t:t\geq0)$ on $\{+,-\}\times\mathbb{R}\cup\infty$ where $J$ is the modulating Markov chain component. First, we study the finiteness of the exponential functional and then consider…

Probability · Mathematics 2020-11-23 Larbi Alili , David Woodford

In this paper we study Green measures of certain classes of Markov processes. In particular Brownian motion and processes with jump generators with different tails. The Green measures are represented as a sum of a singular and a regular…

Probability · Mathematics 2021-01-01 Yuri G. Kondratiev , José L. da Silva

Suppose that $(Z_n)_{n\geq0}$ is a supercritical branching process in independent and identically distributed random environment. The right tail function of the scaled growth rate for $(Z_n)_{n\geq0}$ is studied. The upper bounds for…

Probability · Mathematics 2021-03-02 Yinna Ye

A functional limit theorem is established for the partial-sum process of a class of stationary sequences which exhibit both heavy tails and long-range dependence. The stationary sequence is constructed using multiple stochastic integrals…

Probability · Mathematics 2020-04-09 Shuyang Bai , Takashi Owada , Yizao Wang

We prove a functional limit theorem for Markov chains that, in each step, move up or down by a possibly state dependent constant with probability $1/2$, respectively. The theorem entails that the law of every one-dimensional regular…

Probability · Mathematics 2020-05-13 Stefan Ankirchner , Thomas Kruse , Mikhail Urusov

We develop a general method for extending Markov processes to a larger state space such that the added points form a polar set. The so obtained extension is an improvement on the standard trivial extension in which case the process is made…

Probability · Mathematics 2019-09-06 Lucian Beznea , Iulian Cîmpean , Michael Röckner

The objective of this study is to investigate the limiting behavior of a subgraph counting process. The subgraph counting process we consider counts the number of subgraphs having a specific shape that exist outside an expanding ball as the…

Probability · Mathematics 2016-02-12 Takashi Owada

We present an approach for testing for the existence of continuous generators of discrete stochastic transition matrices. Typically, the known approaches to ascertain the existence of continuous Markov processes are based in the assumption…

Data Analysis, Statistics and Probability · Physics 2016-03-23 Pedro Lencastre , Frank Raischel , Tim Rogers , Pedro G. Lind

A general multi-type population model is considered, where individuals live and reproduce according to their age and type, but also under the influence of the size and composition of the entire population. We describe the dynamics of the…

Probability · Mathematics 2019-03-13 Jie Yen Fan , Kais Hamza , Peter Jagers , Fima C. Klebaner

We extend known saddlepoint tail probability approximations to multivariate cases, including multivariate conditional cases. Our approximation applies to both continuous and lattice variables, and requires the existence of a cumulant…

Statistics Theory · Mathematics 2010-11-29 John Kolassa , Jixin Li