Fisher information approximation of random orthogonal matrices by Gaussian matrices

Let [Formula: see text] be an [Formula: see text] Haar-invariant orthogonal matrix. Let [Formula: see text] be the [Formula: see text] upper-left submatrix of [Formula: see text] and [Formula: see text] be a [Formula: see text] matrix whose [Formula: see text] entries are independent standard normals, where [Formula: see text] and [Formula: see text] are two positive integers. Let [Formula: see text] and [Formula: see text] be their joint distributions, respectively. Consider the Fisher information [Formula: see text] between the distributions of [Formula: see text] and [Formula: see text] In this paper, we conclude that [Formula: see text] as [Formula: see text] if [Formula: see text] and it does not tend to zero if [Formula: see text] Precisely, we obtain that [Formula: see text] when [Formula: see text]

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Publication Details

Journal
Random Matrices Theory and Application
Published
2025-07-25
DOI
https://doi.org/10.1142/s2010326325500212
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
0.00
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article

Fisher information approximation of random orthogonal matrices by Gaussian matrices

Z. Jamie Yao, S. Xie, Yutong Chen, Yutao Ma
Random Matrices Theory and Application
Matrix Theory and Algorithms
article

Fisher information approximation of random orthogonal matrices by Gaussian matrices

Z. Jamie Yao, S. Xie, Yutong Chen, Yutao Ma
article en

Abstract

Let [Formula: see text] be an [Formula: see text] Haar-invariant orthogonal matrix. Let [Formula: see text] be the [Formula: see text] upper-left submatrix of [Formula: see text] and [Formula: see text] be a [Formula: see text] matrix whose [Formula: see text] entries are independent standard normals, where [Formula: see text] and [Formula: see text] are two positive integers. Let [Formula: see text] and [Formula: see text] be their joint distributions, respectively. Consider the Fisher information [Formula: see text] between the distributions of [Formula: see text] and [Formula: see text] In this paper, we conclude that [Formula: see text] as [Formula: see text] if [Formula: see text] and it does not tend to zero if [Formula: see text] Precisely, we obtain that [Formula: see text] when [Formula: see text]

Random Matrices Theory and ApplicationVol. 14(04)
Beijing Normal University (CN)
Openalex Percentile: Top 79%
Matrix Theory and Algorithms
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