Edgeworth expansion and large deviations for the coefficients of products of positive random matrices
Consider the matrix products $G_n: = g_n \ldots g_1$, where $(g_{n})_{n\geq 1}$ is a sequence of independent and identically distributed positive random $d\times d$ matrices. Under the optimal third moment condition, we first establish a Berry-Esseen theorem and an Edgeworth expansion for the $(i,j)...
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Main Authors | , , |
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Format | Journal Article |
Language | English |
Published |
07.09.2022
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Subjects | |
Online Access | Get full text |
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Summary: | Consider the matrix products $G_n: = g_n \ldots g_1$, where $(g_{n})_{n\geq
1}$ is a sequence of independent and identically distributed positive random
$d\times d$ matrices. Under the optimal third moment condition, we first
establish a Berry-Esseen theorem and an Edgeworth expansion for the $(i,j)$-th
entry $G_n^{i,j}$ of the matrix $G_n$, where $1 \leq i, j \leq d$. Using the
Edgeworth expansion for $G_n^{i,j}$ under the changed probability measure, we
then prove precise upper and lower large deviation asymptotics for the entries
$G_n^{i,j}$ subject to an exponential moment assumption. As applications, we
deduce local limit theorems with large deviations for $G_n^{i,j}$ and upper and
lower large deviations bounds for the spectral radius $\rho(G_n)$ of $G_n$. A
byproduct of our approach is the local limit theorem for $G_n^{i,j}$ under the
optimal second moment condition. In the proofs we develop a spectral gap theory
for the norm cocycle and for the coefficients, which is of independent
interest. |
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DOI: | 10.48550/arxiv.2209.03158 |