Non-uniform Edgeworth expansions for weakly dependent random variables and their applications

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: Hafouta, Yeor
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866909894316130304
author Hafouta, Yeor
author_facet Hafouta, Yeor
contents We obtain non-uniform Edgeworth expansions for several classes of weakly dependent (non-stationary) sequences of random variables, including uniformly elliptic inhomogeneous Markov chains, random and time-varying (partially) hyperbolic or expanding dynamical systems, products of random matrices and some classes of local statistics. To the best of our knowledge this is the first time such results are obtained beyond the case of independent summands, even for stationary sequences. As an application of the non uniform expansions we obtain average versions of Edgeworth exapnsions, which provide estimates of the underlying distribution function in $L^p(dx)$ by the standard normal distribution function and its higher order corrections. An additional application is to expansions of expectations $\bbE[h(S_n)]$ of functions $h$ of the underlying sequence $S_n$, whose derivatives grow at most polynomially fast. In particular we provide expansions of the moments of $S_n$ by means the variance of $S_n$. A third application is to Edgeworth expansions in the Wasserstein distance (transport distance). In particular we prove Berry-Esseen theorems in the Wasserstein metrics. This paper compliments \cite{NonU BE} where non-uniform Berry-Esseen theorems were obtained.
format Preprint
id arxiv_https___arxiv_org_abs_2511_06414
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Non-uniform Edgeworth expansions for weakly dependent random variables and their applications
Hafouta, Yeor
Probability
We obtain non-uniform Edgeworth expansions for several classes of weakly dependent (non-stationary) sequences of random variables, including uniformly elliptic inhomogeneous Markov chains, random and time-varying (partially) hyperbolic or expanding dynamical systems, products of random matrices and some classes of local statistics. To the best of our knowledge this is the first time such results are obtained beyond the case of independent summands, even for stationary sequences. As an application of the non uniform expansions we obtain average versions of Edgeworth exapnsions, which provide estimates of the underlying distribution function in $L^p(dx)$ by the standard normal distribution function and its higher order corrections. An additional application is to expansions of expectations $\bbE[h(S_n)]$ of functions $h$ of the underlying sequence $S_n$, whose derivatives grow at most polynomially fast. In particular we provide expansions of the moments of $S_n$ by means the variance of $S_n$. A third application is to Edgeworth expansions in the Wasserstein distance (transport distance). In particular we prove Berry-Esseen theorems in the Wasserstein metrics. This paper compliments \cite{NonU BE} where non-uniform Berry-Esseen theorems were obtained.
title Non-uniform Edgeworth expansions for weakly dependent random variables and their applications
topic Probability
url https://arxiv.org/abs/2511.06414