Limiting behavior of largest entry of random tensor constructed by high-dimensional data
From MaRDI portal
Publication:2209327
DOI10.1007/s10959-019-00958-1zbMath1471.60031arXiv1910.12701OpenAlexW2985096930WikidataQ126853462 ScholiaQ126853462MaRDI QIDQ2209327
Publication date: 30 October 2020
Published in: Journal of Theoretical Probability (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1910.12701
Related Items (4)
Convenient tail bounds for sums of random tensors ⋮ Strong limit theorem for largest entry of large-dimensional random tensor ⋮ Point process convergence for the off-diagonal entries of sample covariance matrices ⋮ Asymptotic distribution of the maximum interpoint distance for high-dimensional data
Cites Work
- Unnamed Item
- On Jiang's asymptotic distribution of the largest entry of a sample correlation matrix
- Limiting laws of coherence of random matrices with applications to testing covariance structure and construction of compressed sensing matrices
- Random tensor theory: Extending random matrix theory to mixtures of random product states
- Two moments suffice for Poisson approximations: The Chen-Stein method
- Central limit theorem for linear eigenvalue statistics for a tensor product version of sample covariance matrices
- The asymptotic distributions of the largest entries of sample correlation matrices.
- From Stein identities to moderate deviations
- Largest entries of sample correlation matrices from equi-correlated normal populations
- The asymptotic distribution and Berry-Esseen bound of a new test for independence in high dimension with an application to stochastic optimization
- Necessary and sufficient conditions for the asymptotic distributions of coherence of ultra-high dimensional random matrices
- Asymptotic theory for maximum deviations of sample covariance matrix estimates
- Some strong limit theorems for the largest entries of sample correlation matrices
- Distributions of Angles in Random Packing on Spheres
- Asymptotic distribution of the largest off-diagonal entry of correlation matrices
- Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings
- Necessary and sufficient conditions for the asymptotic distribution of the largest entry of a sample correlation matrix
This page was built for publication: Limiting behavior of largest entry of random tensor constructed by high-dimensional data