Berry-Esseen bound and precise moderate deviations for products of random matrices

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Xiao, Hui, Grama, Ion, Liu, Quansheng
Natura: Preprint
Pubblicazione: 2019
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866913697010548736
author Xiao, Hui
Grama, Ion
Liu, Quansheng
author_facet Xiao, Hui
Grama, Ion
Liu, Quansheng
contents Let $(g_{n})_{n\geq 1}$ be a sequence of independent and identically distributed (i.i.d.) $d\times d$ real random matrices. For $n\geq 1$ set $G_n = g_n \ldots g_1$. Given any starting point $x=\mathbb R v\in\mathbb{P}^{d-1}$, consider the Markov chain $X_n^x = \mathbb R G_n v $ on the projective space $\mathbb P^{d-1}$ and the norm cocycle $σ(G_n, x)= \log \frac{|G_n v|}{|v|}$, for an arbitrary norm $|\cdot|$ on $\mathbb R^{d}$. Under suitable conditions we prove a Berry-Esseen type theorem and an Edgeworth expansion for the couple $(X_n^x, σ(G_n, x))$. These results are established using a brand new smoothing inequality on complex plane, the saddle point method and additional spectral gap properties of the transfer operator related to the Markov chain $X_n^x$. Cramér type moderate deviation expansions as well as a local limit theorem with moderate deviations are proved for the couple $(X_n^x, σ(G_n, x))$ with a target function $φ$ on the Markov chain $X_n^x$.
format Preprint
id arxiv_https___arxiv_org_abs_1907_02438
institution arXiv
publishDate 2019
record_format arxiv
spellingShingle Berry-Esseen bound and precise moderate deviations for products of random matrices
Xiao, Hui
Grama, Ion
Liu, Quansheng
Probability
Let $(g_{n})_{n\geq 1}$ be a sequence of independent and identically distributed (i.i.d.) $d\times d$ real random matrices. For $n\geq 1$ set $G_n = g_n \ldots g_1$. Given any starting point $x=\mathbb R v\in\mathbb{P}^{d-1}$, consider the Markov chain $X_n^x = \mathbb R G_n v $ on the projective space $\mathbb P^{d-1}$ and the norm cocycle $σ(G_n, x)= \log \frac{|G_n v|}{|v|}$, for an arbitrary norm $|\cdot|$ on $\mathbb R^{d}$. Under suitable conditions we prove a Berry-Esseen type theorem and an Edgeworth expansion for the couple $(X_n^x, σ(G_n, x))$. These results are established using a brand new smoothing inequality on complex plane, the saddle point method and additional spectral gap properties of the transfer operator related to the Markov chain $X_n^x$. Cramér type moderate deviation expansions as well as a local limit theorem with moderate deviations are proved for the couple $(X_n^x, σ(G_n, x))$ with a target function $φ$ on the Markov chain $X_n^x$.
title Berry-Esseen bound and precise moderate deviations for products of random matrices
topic Probability
url https://arxiv.org/abs/1907.02438