Moderate Deviation Principle for a Stochastic Approximation Process

Fuente: arXiv
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Main Authors: Shi, Jianan, Yin, Qing, Miao, Yu
Format: Preprint
Published: 2026
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author Shi, Jianan
Yin, Qing
Miao, Yu
author_facet Shi, Jianan
Yin, Qing
Miao, Yu
contents In this paper, we investigate a stochastic approximation procedure $\left(X_n\right)_{n\ge 0}$ taking values in $R$. The process is adapted to a filtration $(F_n)_{n\ge 0}$ and satisfies the recursion $X_{n+1}=X_n+\frac{b}{n+1}\big[g(X_n)+U_{n+1}\big]$, where $b>0$, $g:R \to R$ is a function and $\left(U_n\right)_{n\ge 1}$ is a sequence of bounded martingale differences adapted to the filtration $(F_n)_{n\ge 1}$. We establish the moderate deviation principle for the stochastic process $(X_n)_{n\ge 0}$. As auxiliary results, we also obtain the exponential inequality for $(X_n)_{n\ge 0}$ and the moderate deviation principle for weighted sums of bounded martingale differences.
format Preprint
id arxiv_https___arxiv_org_abs_2605_07369
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Moderate Deviation Principle for a Stochastic Approximation Process
Shi, Jianan
Yin, Qing
Miao, Yu
Probability
In this paper, we investigate a stochastic approximation procedure $\left(X_n\right)_{n\ge 0}$ taking values in $R$. The process is adapted to a filtration $(F_n)_{n\ge 0}$ and satisfies the recursion $X_{n+1}=X_n+\frac{b}{n+1}\big[g(X_n)+U_{n+1}\big]$, where $b>0$, $g:R \to R$ is a function and $\left(U_n\right)_{n\ge 1}$ is a sequence of bounded martingale differences adapted to the filtration $(F_n)_{n\ge 1}$. We establish the moderate deviation principle for the stochastic process $(X_n)_{n\ge 0}$. As auxiliary results, we also obtain the exponential inequality for $(X_n)_{n\ge 0}$ and the moderate deviation principle for weighted sums of bounded martingale differences.
title Moderate Deviation Principle for a Stochastic Approximation Process
topic Probability
url https://arxiv.org/abs/2605.07369