Joint CLT for top eigenvalues of sample covariance matrices of separable high dimensional long memory processes
From MaRDI portal
Publication:5092968
DOI10.1142/S2010326322500320zbMath1493.15117arXiv1906.00909OpenAlexW2947375302MaRDI QIDQ5092968
Publication date: 26 July 2022
Published in: Random Matrices: Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1906.00909
Stationary stochastic processes (60G10) Eigenvalues, singular values, and eigenvectors (15A18) Random matrices (algebraic aspects) (15B52) Integral equations of the convolution type (Abel, Picard, Toeplitz and Wiener-Hopf type) (45E10) Toeplitz, Cauchy, and related matrices (15B05)
Related Items
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Gaussian fluctuations for linear spectral statistics of large random covariance matrices
- Tracy-Widom distribution for the largest eigenvalue of real sample covariance matrices with general population
- Functional CLT for sample covariance matrices
- Anisotropic local laws for random matrices
- Central limit theorems for eigenvalues in a spiked population model
- On sample eigenvalues in a generalized spiked population model
- Central limit theorem for linear spectral statistics of general separable sample covariance matrices with applications
- Algebraic multiplicity of eigenvalues of linear operators
- No eigenvalues outside the support of the limiting empirical spectral distribution of a separable covariance matrix
- PCA consistency in high dimension, low sample size context
- On the limit of the largest eigenvalue of the large dimensional sample covariance matrix
- Some limit theorems for the eigenvalues of a sample covariance matrix
- On the eigenvalues of integral operators with difference kernels
- The strong limits of random matrix spectra for sample matrices of independent elements
- No eigenvalues outside the support of the limiting spectral distribution of large-dimensional sample covariance matrices
- CLT for largest eigenvalues and unit root testing for high-dimensional nonstationary time series
- Limiting spectral distribution for a class of random matrices
- On the distribution of the largest eigenvalue in principal components analysis
- CLT for linear spectral statistics of large-dimensional sample covariance matrices.
- On the empirical distribution of eigenvalues of a class of large dimensional random matrices
- Analysis of the limiting spectral distribution of large dimensional random matrices
- Strong convergence of the empirical distribution of eigenvalues of large dimensional random matrices
- Shape fluctuations and random matrices
- Unbounded largest eigenvalue of large sample covariance matrices: asymptotics, fluctuations and applications
- Asymptotics of empirical eigenstructure for high dimensional spiked covariance
- Spiked separable covariance matrices and principal components
- Limiting laws for divergent spiked eigenvalues and largest nonspiked eigenvalue of sample covariance matrices
- Edge universality of separable covariance matrices
- Universality for the largest eigenvalue of sample covariance matrices with general population
- Tracy-Widom limit for the largest eigenvalue of a large class of complex sample covariance matrices
- Central limit theorem for linear spectral statistics of large dimensional separable sample covariance matrices
- Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices
- Analysis of the limiting spectral measure of large random matrices of the separable covariance type
- The Central Limit Theorem for Linear Eigenvalue Statistics of the Sum of Independent Matrices of Rank One
- Probability Inequalities for the Sum of Independent Random Variables
- Theorems and Fallacies in the Theory of Long-Range-Dependent Processes
- Long-Range Dependence and Self-Similarity
- DISTRIBUTION OF EIGENVALUES FOR SOME SETS OF RANDOM MATRICES