Strong stationary times for one-dimensional diffusions

IF 1.2 2区 数学 Q2 STATISTICS & PROBABILITY Annales De L Institut Henri Poincare-probabilites Et Statistiques Pub Date : 2013-11-25 DOI:10.1214/16-aihp745
L. Miclo
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引用次数: 15

Abstract

A necessary and sufficient condition is obtained for the existence of strong stationary times for ergodic one-dimensional diffusions, whatever the initial distribution. The strong stationary times are constructed through intertwinings with dual processes, in the Diaconis-Fill sense, taking values in the set of segments of the extended line $\mathbb{R}\sqcup\{-\infty,+\infty\}$. They can be seen as natural $h$-transforms of the extensions to the diffusion framework of the evolving sets of Morris-Peres. Starting from a singleton set, the dual process begins by evolving into true segments in the same way a Bessel process of dimension 3 escapes from 0. The strong stationary time corresponds to the first time the full segment $[-\infty,+\infty]$ is reached. The benchmark Ornstein-Uhlenbeck process cannot be treated in this way, it will nevertheless be seen how to use other strong times to recover its optimal exponential rate of convergence in the total variation sense.
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一维扩散的强平稳时间
得到了遍历一维扩散存在强平稳时间的一个充分必要条件,无论初始分布如何。在Diaconis-Fill意义上,强平稳时间是通过与双重过程的交织来构建的,在延长线$\mathbb{R}\sqcup\{-\infty,+\infty\}$的一组片段中取值。它们可以被看作是Morris-Peres演化集合的扩散框架扩展的自然$h$变换。从单例集开始,双过程以与3维贝塞尔过程从0转义相同的方式开始演变为真段。强平稳时间对应于第一次到达完整段$[-\infty,+\infty]$。基准的Ornstein-Uhlenbeck过程不能这样处理,但我们可以看到如何利用其他强时间来恢复其在总变分意义上的最优指数收敛速度。
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来源期刊
CiteScore
2.70
自引率
0.00%
发文量
85
审稿时长
6-12 weeks
期刊介绍: The Probability and Statistics section of the Annales de l’Institut Henri Poincaré is an international journal which publishes high quality research papers. The journal deals with all aspects of modern probability theory and mathematical statistics, as well as with their applications.
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