Joint Central Limit Theorem for Eigenvalue Statistics from Several Dependent Large Dimensional Sample Covariance Matrices with Application
Author:
Affiliation:
1. School of Statistics and Management Shanghai University of Finance and Economics
2. Department of Statistics Pennsylvania State University
3. Department of Statistics and Actuarial Science The University of Hong Kong
Funder
National Natural Science Foundation of China
National Science Foundation
Publisher
Wiley
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1111/sjos.12320
Reference18 articles.
1. No eigenvalues outside the support of the limiting spectral distribution of large-dimensional sample covariance matrices
2. CLT for linear spectral statistics of large-dimensional sample covariance matrices
3. Spectral Analysis of Large Dimensional Random Matrices
4. A note on the limiting spectral distribution of a symmetrized auto-cross covariance matrix
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4. Smallest singular value and limit eigenvalue distribution of a class of non-Hermitian random matrices with statistical application;Journal of Multivariate Analysis;2020-07
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