Hypothesis testing for high-dimensional covariance matrices

Weiming Li; Yingli Qin

doi:10.1016/j.jmva.2014.03.013

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Hypothesis testing for high-dimensional covariance matrices

Weiming Li Yingli Qin

Year: 2014 Journal: Journal of Multivariate Analysis Vol: 128 Pages: 108-119 Publisher: Elsevier BV

DOI: 10.1016/j.jmva.2014.03.013

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Keywords:

Mathematics Identity matrix Dimension (graph theory) Covariance matrix Covariance Estimation of covariance matrices Statistics Sample size determination Law of total covariance Statistical hypothesis testing Covariance function Applied mathematics Matrix (chemical analysis) Matérn covariance function Scatter matrix Sample (material) Covariance intersection Combinatorics Eigenvalues and eigenvectors

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Random Matrices and Applications

Physical Sciences → Mathematics → Statistics and Probability

Bayesian Methods and Mixture Models

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Combinatorial Mathematics

Physical Sciences → Mathematics → Discrete Mathematics and Combinatorics

Hypothesis testing for high-dimensional covariance matrices

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