Logarithmic law of large random correlation matrices
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Publication:6178564
DOI10.3150/23-bej1600arXiv2103.13900MaRDI QIDQ6178564
Nestor Parolya, Johannes Heiny, Dorota Kurowicka
Publication date: 16 January 2024
Published in: Bernoulli (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2103.13900
random matrix theorydependent datasample correlation matrixCLTlog determinantlarge-dimensional asymptotic
Multivariate analysis (62Hxx) Limit theorems in probability theory (60Fxx) Probability theory on algebraic and topological structures (60Bxx)
Cites Work
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- Estimation of the global minimum variance portfolio in high dimensions
- Gaussian fluctuations for linear spectral statistics of large random covariance matrices
- On the sphericity test with large-dimensional observations
- Central limit theorems for classical likelihood ratio tests for high-dimensional normal distributions
- A new test of independence for high-dimensional data
- A central limit theorem for the determinant of a Wigner matrix
- On Jiang's asymptotic distribution of the largest entry of a sample correlation matrix
- Tracy-Widom law for the extreme eigenvalues of sample correlation matrices
- Limiting laws of coherence of random matrices with applications to testing covariance structure and construction of compressed sensing matrices
- Generating random correlation matrices based on partial correlations
- Spectral analysis of large dimensional random matrices
- Concentration of measure and spectra of random matrices: applications to correlation matrices, elliptical distributions and beyond
- Almost sure convergence of the largest and smallest eigenvalues of high-dimensional sample correlation matrices
- CLT for linear spectral statistics of large-dimensional sample covariance matrices.
- The asymptotic distributions of the largest entries of sample correlation matrices.
- Thin-shell theory for rotationally invariant random simplices
- Large sample correlation matrices: a comparison theorem and its applications
- Likelihood ratio tests under model misspecification in high dimensions
- Likelihood ratio tests for many groups in high dimensions
- Point process convergence for the off-diagonal entries of sample covariance matrices
- Testing for independence of large dimensional vectors
- Substitution principle for CLT of linear spectral statistics of high-dimensional sample covariance matrices with applications to hypothesis testing
- The asymptotic distribution and Berry-Esseen bound of a new test for independence in high dimension with an application to stochastic optimization
- The logarithmic law of sample covariance matrices near singularity
- Determinant of sample correlation matrix with application
- Random matrices: law of the determinant
- The logarithmic law of random determinant
- Likelihood Ratio Tests for High‐Dimensional Normal Distributions
- Testing for complete independence in high dimensions
- Asymptotic distribution of the largest off-diagonal entry of correlation matrices
- On moments of quadratic forms in non-spherically distributed variables
- Limit theorems for random simplices in high dimensions
- The distribution of volume reductions induced by isotropic random projections
- Large Sample Covariance Matrices and High-Dimensional Data Analysis
- A Dynamical Approach to Random Matrix Theory
- The Distribution of the Determinant of a Complex Wishart Distributed Matrix
- High Dimensional Correlation Matrices: The Central Limit Theorem and Its Applications
- The asymptotic distribution of the determinant of a random correlation matrix
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