On the eigenvectors of large-dimensional sample spatial sign covariance matrices
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Publication:2101471
DOI10.1016/j.jmva.2022.105119OpenAlexW4307211187MaRDI QIDQ2101471
Publication date: 6 December 2022
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmva.2022.105119
random matrixcentral limit theoremseigenvectors and eigenvaluesHaar distributionspatial sign covariance matrix
Cites Work
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- Robustifying principal component analysis with spatial sign vectors
- Weak convergence of random functions defined by the eigenvectors of sample covariance matrices
- Spectral analysis of large dimensional random matrices
- On the limit of the largest eigenvalue of the large dimensional sample covariance matrix
- On the eigenvectors of large dimensional sample covariance matrices
- Robust principal component analysis for functional data. (With comments)
- No eigenvalues outside the support of the limiting spectral distribution of large-dimensional sample covariance matrices
- Exact separation of eigenvalues of large dimensional sample covariance matrices
- On the distribution of the largest eigenvalue in principal components analysis
- CLT for linear spectral statistics of large-dimensional sample covariance matrices.
- Strong convergence of the empirical distribution of eigenvalues of large dimensional random matrices
- On eigenvalues of a high-dimensional spatial-sign covariance matrix
- The spatial sign covariance matrix with unknown location
- Spatial sign correlation
- On asymptotics of eigenvectors of large sample covariance matrix
- Convergence rates of eigenvector empirical spectral distribution of large dimensional sample covariance matrix
- Robust functional estimation using the median and spherical principal components
- The asymptotic inadmissibility of the spatial sign covariance matrix for elliptically symmetric distributions
- The Estimation of Leverage Effect With High-Frequency Data
- Sign and rank covariance matrices
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