Uniform convergence of conditional distributions for one-dimensional diffusion processes

Fuente: arXiv
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Auteurs principaux: He, Guoman, Zhang, Hanjun
Format: Preprint
Publié: 2022
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author He, Guoman
Zhang, Hanjun
author_facet He, Guoman
Zhang, Hanjun
contents 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 distribution of the process converges to its unique quasi-stationary distribution exponentially fast in the total variation norm, uniformly with respect to the initial distribution. Moreover, we also use the same method to show that the conditional distribution of the process converges exponentially fast in the $ψ$-norm to the unique quasi-stationary distribution. The rate of convergence of the conditional empirical measure to the quasi-ergodic distribution is also considered. Finally, two examples arising in population dynamics are also given to illustrate the main results.
format Preprint
id arxiv_https___arxiv_org_abs_2208_08911
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Uniform convergence of conditional distributions for one-dimensional diffusion processes
He, Guoman
Zhang, Hanjun
Probability
Primary 60J60, Secondary 60B10, 37A25
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 distribution of the process converges to its unique quasi-stationary distribution exponentially fast in the total variation norm, uniformly with respect to the initial distribution. Moreover, we also use the same method to show that the conditional distribution of the process converges exponentially fast in the $ψ$-norm to the unique quasi-stationary distribution. The rate of convergence of the conditional empirical measure to the quasi-ergodic distribution is also considered. Finally, two examples arising in population dynamics are also given to illustrate the main results.
title Uniform convergence of conditional distributions for one-dimensional diffusion processes
topic Probability
Primary 60J60, Secondary 60B10, 37A25
url https://arxiv.org/abs/2208.08911