Edgeworth Expansion and Large Deviations for the Coefficients of Products of Positive Random Matrices

Consider the matrix products G n : = g n ⋯ g 1 , where ( g n ) n ⩾ 1 is a sequence of independent and identically distributed positive random d × 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...

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Published inJournal of theoretical probability Vol. 38; no. 2
Main Authors Xiao, Hui, Grama, Ion, Liu, Quansheng
Format Journal Article
LanguageEnglish
Published New York Springer US 01.06.2025
Springer Nature B.V
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Abstract Consider the matrix products G n : = g n ⋯ g 1 , where ( g n ) n ⩾ 1 is a sequence of independent and identically distributed positive random d × 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 ⩽ i , j ⩽ d . Utilizing 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 establish upper and lower large deviations bounds for the spectral radius ρ ( 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 both the norm cocycle and the coefficients, which is of independent interest.
AbstractList Consider the matrix products G n : = g n ⋯ g 1 , where ( g n ) n ⩾ 1 is a sequence of independent and identically distributed positive random d × 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 ⩽ i , j ⩽ d . Utilizing 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 establish upper and lower large deviations bounds for the spectral radius ρ ( 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 both the norm cocycle and the coefficients, which is of independent interest.
Consider the matrix products Gn:=gn⋯g1, where (gn)n⩾1 is a sequence of independent and identically distributed positive random d×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 Gni,j of the matrix Gn, where 1⩽i,j⩽d. Utilizing the Edgeworth expansion for Gni,j under the changed probability measure, we then prove precise upper and lower large deviation asymptotics for the entries Gni,j subject to an exponential moment assumption. As applications, we deduce local limit theorems with large deviations for Gni,j and establish upper and lower large deviations bounds for the spectral radius ρ(Gn) of Gn. A byproduct of our approach is the local limit theorem for Gni,j under the optimal second moment condition. In the proofs we develop a spectral gap theory for both the norm cocycle and the coefficients, which is of independent interest.
ArticleNumber 38
Author Grama, Ion
Liu, Quansheng
Xiao, Hui
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Issue 2
Keywords Berry–Esseen theorem
Primary 60F05
Spectral gap
60F10
Edgeworth expansion
Precise large deviations
Secondary 60J05
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Products of positive random matrices
Local limit theorem
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Snippet Consider the matrix products G n : = g n ⋯ g 1 , where ( g n ) n ⩾ 1 is a sequence of independent and identically distributed positive random d × d matrices....
Consider the matrix products Gn:=gn⋯g1, where (gn)n⩾1 is a sequence of independent and identically distributed positive random d×d matrices. Under the optimal...
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SubjectTerms Deviation
Mathematics
Mathematics and Statistics
Probability Theory and Stochastic Processes
Statistics
Theorems
Title Edgeworth Expansion and Large Deviations for the Coefficients of Products of Positive Random Matrices
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