Smallest singular value and limit eigenvalue distribution of a class of non-Hermitian random matrices with statistical application

DOI10.1016/j.jmva.2020.104623zbMath1439.60009arXiv1812.07237OpenAlexW3014890358MaRDI QIDQ2181731

Walid Hachem, Arup Bose

Publication date: 19 May 2020

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1812.07237

zbMATH Keywords

smallest singular valuelimit spectral distributionlarge non-Hermitian matrix theorywhiteness test in multivariate time series

Mathematics Subject Classification ID

Hypothesis testing in multivariate analysis (62H15) Random matrices (probabilistic aspects) (60B20) Eigenvalues, singular values, and eigenvectors (15A18) Random matrices (algebraic aspects) (15B52)

Related Items (6)

Spectral measure of empirical autocovariance matrices of high-dimensional Gaussian stationary processes ⋮ Singular value distribution of dense random matrices with block Markovian dependence ⋮ Unnamed Item ⋮ Universality of the least singular value for the sum of random matrices ⋮ The asymptotic distribution of the condition number for random circulant matrices ⋮ On eigenvalue distributions of large autocovariance matrices

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