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This article studies the quasi-stationary behaviour of absorbed one-dimensional diffusions. We obtain necessary and sufficient conditions for the exponential convergence to a unique quasi-stationary distribution in total variation,…

Probability · Mathematics 2017-03-03 Nicolas Champagnat , Denis Villemonais

For general, almost surely absorbed Markov processes, we obtain necessary and sufficient conditions for exponential convergence to a unique quasi-stationary distribution in the total variation norm. These conditions also ensure the…

Probability · Mathematics 2014-12-25 Nicolas Champagnat , Denis Villemonais

In this paper, we study the quasi-stationary behavior of the one-dimensional diffusion process with a regular or exit boundary at 0 and an entrance boundary at $\infty$. By using the Doob's $h$-transform, we show that the conditional…

Probability · Mathematics 2025-10-15 Guoman He , Hanjun Zhang

This paper studies the quasi-stationary distributions for a single death process (or downwardly skip-free process) with killing defined on the non-negative integers, corresponding to a non-conservative transition rate matrix. The set…

Probability · Mathematics 2024-08-13 Zhe-Kang Fang , Yong-Hua Mao

We extend some results on the convergence of one-dimensional diffusions killed at the boundary, conditioned on extended survival, to the case of general killing on the interior. We show, under fairly general conditions, that a diffusion…

Probability · Mathematics 2007-05-23 David Steinsaltz , Steven N. Evans

We establish sufficient conditions for exponential convergence to a unique quasi-stationary distribution in the total variation norm. These conditions also ensure the existence and exponential ergodicity of the Q-process, the process…

Probability · Mathematics 2023-08-01 Aurélien Velleret

We consider general Markov processes with absorption and provide criteria ensuring the exponential convergence in total variation of the distribution of the process conditioned not to be absorbed. The first one is based on two-sided…

Probability · Mathematics 2018-01-18 Nicolas Champagnat , Koléhè Coulibaly-Pasquier , Denis Villemonais

For Markov processes with absorption, we provide general criteria ensuring the existence and the exponential non-uniform convergence in total variation norm to a quasi-stationary distribution. We also characterize a subset of its domain of…

Probability · Mathematics 2022-10-24 Nicolas Champagnat , Denis Villemonais

This article studies the quasi-stationary behaviour of multidimensional birth and death processes, modeling the interaction between several species, absorbed when one of the coordinates hits 0. We study models where the absorption rate is…

Probability · Mathematics 2015-08-14 Nicolas Champagnat , Denis Villemonais

In this paper, we study quasi-stationary distributions (QSDs) for one-dimensional diffusions killed at 0, when 0 is a regular boundary and $+\infty$ is a natural boundary. More precisely, we not only give a necessary and sufficient…

Probability · Mathematics 2015-12-31 Hanjun Zhang , Guoman He

We study quasi-stationarity for one-dimensional diffusions killed at 0, when 0 is a regular boundary and $+\infty$ is an entrance boundary. We give a necessary and sufficient condition for the existence of exactly one quasi-stationary…

Probability · Mathematics 2016-03-16 Hanjun Zhang , Guoman He

For a time-changed symmetric $\alpha$-stable process killed upon hitting zero, under the condition of entrance from infinity, we prove the existence and uniqueness of quasi-stationary distribution (QSD). The exponential convergence to the…

Probability · Mathematics 2023-06-14 Zhe-Kang Fang , Yong-Hua Mao , Tao Wang

In this paper, we study quasi-stationarity for a large class of Kolmogorov diffusions. The main novelty here is that we allow the drift to go to $- \infty$ at the origin, and the diffusion to have an entrance boundary at $+\infty$. These…

We study the probabilistic evolution of a birth and death continuous time measure-valued process with mutations and ecological interactions. The individuals are characterized by (phenotypic) traits that take values in a compact metric…

Probability · Mathematics 2009-04-23 Pierre Collet , Servet Martinez , Sylvie Méléard , Jaime San Martin

This article studies the quasi-stationary behaviour of population processes with unbounded absorption rate, including one-dimensional birth and death processes with catastrophes and multi-dimensional birth and death processes, modeling…

Probability · Mathematics 2016-11-10 Nicolas Champagnat , Denis Villemonais

In a first part, we prove a Lyapunov-type criterion for the $\xi\_1$-positive recurrence of absorbed birth and death processes and provide new results on the domain of attraction of the minimal quasi-stationary distribution. In a second…

Probability · Mathematics 2015-01-29 Denis Villemonais

This paper extends and clarifies results of Steinsaltz and Evans [Trans. Amer. Math. Soc. 359 (2007) 1285-1234], which found conditions for convergence of a killed one-dimensional diffusion conditioned on survival, to a quasistationary…

Probability · Mathematics 2015-03-17 Martin Kolb , David Steinsaltz

This paper gives foundational results for the application of quasi-stationarity to Monte Carlo inference problems. We prove natural sufficient conditions for the quasi-limiting distribution of a killed diffusion to coincide with a target…

Methodology · Statistics 2018-12-07 Andi Q. Wang , Martin Kolb , Gareth O. Roberts , David Steinsaltz

The present paper is devoted to the investigation of the long term behavior of a class of singular multi-dimensional diffusion processes that get absorbed in finite time with probability one. Our focus is on the analysis of quasi-stationary…

Probability · Mathematics 2021-02-12 Alexandru Hening , Weiwei Qi , Zhongwei Shen , Yingfei Yi

We study the long time behaviour of a Markov process evolving in $\mathbb{N}$ and conditioned not to hit 0. Assuming that the process comes back quickly from infinity, we prove that the process admits a unique quasi-stationary distribution…

Probability · Mathematics 2013-04-04 Servet Martinez , Jaime San Martin , Denis Villemonais
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