Probability and Moment Inequalities for Additive Functionals of Geometrically Ergodic Markov Chains

IF 0.8 4区 数学 Q3 STATISTICS & PROBABILITY
Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov
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引用次数: 0

Abstract

In this paper, we establish moment and Bernstein-type inequalities for additive functionals of geometrically ergodic Markov chains. These inequalities extend the corresponding inequalities for independent random variables. Our conditions cover Markov chains converging geometrically to the stationary distribution either in weighted total variation norm or in weighted Wasserstein distances. Our inequalities apply to unbounded functions and depend explicitly on constants appearing in the conditions that we consider.

几何尔格马尔可夫链加法函数的概率和矩不等式
在本文中,我们为几何遍历马尔可夫链的加法函数建立了矩不等式和伯恩斯坦型不等式。这些不等式扩展了独立随机变量的相应不等式。我们的条件涵盖了以加权总变异规范或加权瓦瑟斯坦距离几何收敛于静态分布的马尔科夫链。我们的不等式适用于无界函数,并明确取决于我们所考虑的条件中出现的常数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Theoretical Probability
Journal of Theoretical Probability 数学-统计学与概率论
CiteScore
1.50
自引率
12.50%
发文量
65
审稿时长
6-12 weeks
期刊介绍: Journal of Theoretical Probability publishes high-quality, original papers in all areas of probability theory, including probability on semigroups, groups, vector spaces, other abstract structures, and random matrices. This multidisciplinary quarterly provides mathematicians and researchers in physics, engineering, statistics, financial mathematics, and computer science with a peer-reviewed forum for the exchange of vital ideas in the field of theoretical probability.
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