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Related papers: Yaglom Limit via Holley Inequality

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In this paper we prove a weak necessary and sufficient maximum principle for Markovian regime switching stochastic optimal control problems. Instead of insisting on the maximum condition of the Hamiltonian, we show that 0 belongs to the sum…

Optimization and Control · Mathematics 2013-09-17 Yusong Li , Harry Zheng

We consider a slightly subcritical branching Brownian motion with absorption, where particles move as Brownian motions with drift $-\sqrt{2+2\varepsilon}$, undergo dyadic fission at rate $1$, and are killed when they reach the origin. We…

Probability · Mathematics 2022-01-25 Jiaqi Liu

We study the asymptotics of the survival probability for the critical and decomposable branching processes in random environment and prove Yaglom type limit theorems for these processes. It is shown that such processes possess some…

Probability · Mathematics 2014-03-05 Vladimir Vatutin , Quansheng Liu

In the continuity of a recent paper ([6]), dealing with finite Markov chains, this paper proposes and analyzes a recursive algorithm for the approximation of the quasi-stationary distribution of a general Markov chain living on a compact…

Probability · Mathematics 2017-11-15 Michel Benaim , Bertrand Cloez , Fabien Panloup

We study the long-time behavior of stochastic models with an absorbing state, conditioned on survival. For a large class of processes, in which saturation prevents unlimited growth, statistical properties of the surviving sample attain…

Statistical Mechanics · Physics 2009-11-07 Ronald Dickman , Ronaldo Vidigal

An algorithm for estimating quasi-stationary distribution of finite state space Markov chains has been proven in a previous paper. Now this paper proves a similar algorithm that works for general state space Markov chains under very general…

Probability · Mathematics 2015-03-04 Jose H. Blanchet , Peter Glynn , Shuheng Zheng

In this paper, we consider chains of infinite order on countable state spaces with prohibited transitions. We give a set of sufficient conditions on the structure of the probability kernels of the chains to have at most one stationary…

Probability · Mathematics 2026-05-22 Christophe Gallesco , Sandro Gallo , Daniel Yasumasa Takahashi

In this short note we provide an elementary proof that a certain type of nonuniform sequential Doeblin minorization condition implies non-uniform sequential "geometric" ergodicity. Using this result several limit theorems for inhomogeneous…

Probability · Mathematics 2025-10-20 Yeor Hafouta , Brenden Williams

This paper is a survey of various proofs of the so called {\em fundamental theorem of Markov chains}: every ergodic Markov chain has a unique positive stationary distribution and the chain attains this distribution in the limit independent…

Probability · Mathematics 2022-04-05 Somenath Biswas

In this paper, we investigate the asymptotic behavior of continuous-state branching processes in a Brownian random environment (CBBRE) conditioned on non-extinction. For the subcritical case, we prove the existence of the Yaglom limit and…

Probability · Mathematics 2026-05-28 Pei-Sen Li , Xiangqi Zheng , Xiaowen Zhou

Biological systems use energy to maintain non-equilibrium distributions for long times, e.g. of chemical concentrations or protein conformations. What are the fundamental limits of the power used to "hold" a stochastic system in a desired…

Statistical Mechanics · Physics 2019-07-04 Dmitri S. Pavlichin , Yihui Quek , Tsachy Weissman

For the critical branching random walk in $\mathbb{Z}^{4}$ with branching at the origin only we find the asymptotic behavior of the probability of the event that there are particles at the origin at moment $t\rightarrow \infty $ and prove a…

Probability · Mathematics 2010-07-28 Yueyun Hu , Vladimir Vatutin , Valentin Topchii

We study the existence and the exponential ergodicity of a general interacting particle system, whose components are driven by independent diffusion processes with values in an open subset of $\mathds{R}^d$, $d\geq 1$. The interaction…

Probability · Mathematics 2010-12-01 Denis Villemonais

We consider a class of optimal control problems, with finite or infinite horizon, for a continuous-time Markov chain with finite state space. In this case, the control process affects the transition rates. We suppose that the controlled…

Optimization and Control · Mathematics 2026-02-19 Fulvia Confortola , Marco Fuhrman

For Markov chains and Markov processes exhibiting a form of stochastic monotonicity (larger states shift up transition probabilities in terms of stochastic dominance), stability and ergodicity results can be obtained using order-theoretic…

Probability · Mathematics 2024-10-01 Takashi Kamihigashi , John Stachurski

We derive a finite-sample probabilistic bound on the parameter estimation error of a system identification algorithm for Linear Switched Systems. The algorithm estimates Markov parameters from a single trajectory and applies a variant of…

Machine Learning · Computer Science 2025-05-19 Daniel Racz , Mihaly Petreczky , Balint Daroczy

Using elementary methods, we prove that for a countable Markov chain $P$ of ergodic degree $d > 0$ the rate of convergence towards the stationary distribution is subgeometric of order $n^{-d}$, provided the initial distribution satisfies…

Probability · Mathematics 2007-05-23 Stefano Isola

We consider a controlled-diffusion process pertaining to a chain of distributed systems with random perturbations that satisfies a weak H\"ormander type condition. In particular, we consider a stochastic control problem with the following…

Optimization and Control · Mathematics 2015-09-29 Getachew K. Befekadu , Eduardo L. Pasiliao

A block Markov chain is a Markov chain whose state space can be partitioned into a finite number of clusters such that the transition probabilities only depend on the clusters. Block Markov chains thus serve as a model for Markov chains…

Probability · Mathematics 2023-04-03 Jaron Sanders , Alexander Van Werde

We provide a nonasymptotic analysis of convergence to stationarity for a collection of Markov chains on multivariate state spaces, from arbitrary starting points, thereby generalizing results in [Khare and Zhou Ann. Appl. Probab. 19 (2009)…

Probability · Mathematics 2013-02-25 Kshitij Khare , Nabanita Mukherjee