Bernstein-type Inequalities for Markov Chains and Markov Processes: A Simple and Robust Proof

Fuente: arXiv
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Main Authors: Huang, De, Li, Xiangyuan
Format: Preprint
Published: 2024
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author Huang, De
Li, Xiangyuan
author_facet Huang, De
Li, Xiangyuan
contents We establish a new Bernstein-type deviation inequality for general (non-reversible) discrete-time Markov chains via an elementary approach. More robust than existing works in the literature, our result only requires the Markov chain to satisfy an iterated Poincaré inequality. Moreover, our method can be readily generalized to continuous-time Markov processes.
format Preprint
id arxiv_https___arxiv_org_abs_2408_04930
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Bernstein-type Inequalities for Markov Chains and Markov Processes: A Simple and Robust Proof
Huang, De
Li, Xiangyuan
Probability
60J05, 60J25, 37A30
We establish a new Bernstein-type deviation inequality for general (non-reversible) discrete-time Markov chains via an elementary approach. More robust than existing works in the literature, our result only requires the Markov chain to satisfy an iterated Poincaré inequality. Moreover, our method can be readily generalized to continuous-time Markov processes.
title Bernstein-type Inequalities for Markov Chains and Markov Processes: A Simple and Robust Proof
topic Probability
60J05, 60J25, 37A30
url https://arxiv.org/abs/2408.04930