Applications on linear spectral statistics of high-dimensional sample covariance matrix with divergent spectrum

DOI10.1016/j.csda.2022.107617OpenAlexW4296605717MaRDI QIDQ2101405

Yanyan Li

Publication date: 6 December 2022

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2022.107617

zbMATH Keywords

random matrix theoryspiked population modelpopulation spectral distribution

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• A test for the equality of covariance matrices when the dimension is large relative to the sample sizes
• Two sample tests for high-dimensional covariance matrices
• On high-dimensional sign tests
• On the sphericity test with large-dimensional observations
• Estimation of the population spectral distribution from a large dimensional sample covariance matrix
• Central limit theorem for linear spectral statistics of large dimensional Kendall's rank correlation matrices and its applications
• Central limit theorem for signal-to-interference ratio of reduced rank linear receiver
• A supplement on CLT for LSS under a large dimensional generalized spiked covariance model
• High-dimensional covariance matrices in elliptical distributions with application to spherical test
• On the distribution of the largest eigenvalue in principal components analysis
• Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size
• CLT for linear spectral statistics of large-dimensional sample covariance matrices.
• CLT for linear spectral statistics of high-dimensional sample covariance matrices in elliptical distributions
• Limiting laws for divergent spiked eigenvalues and largest nonspiked eigenvalue of sample covariance matrices
• Substitution principle for CLT of linear spectral statistics of high-dimensional sample covariance matrices with applications to hypothesis testing
• ESTIMATION OF SPIKED EIGENVALUES IN SPIKED MODELS
• Improved Estimation of Eigenvalues and Eigenvectors of Covariance Matrices Using Their Sample Estimates
• Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings
• ON ESTIMATION OF THE POPULATION SPECTRAL DISTRIBUTION FROM A HIGH‐DIMENSIONAL SAMPLE COVARIANCE MATRIX
• On Estimation of the Noise Variance in High Dimensional Probabilistic Principal Component Analysis
• Multivariate sign-based high-dimensional tests for sphericity
• A local moment estimator of the spectrum of a large dimensional covariance matrix

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