An exact test about the covariance matrix

DOI10.1016/j.jmva.2013.12.007zbMath1280.62066OpenAlexW2155301656MaRDI QIDQ2637609

Taras Bodnar, Arjun K. Gupta

Publication date: 13 February 2014

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

Full work available at URL: https://doi.org/10.1016/j.jmva.2013.12.007

zbMATH Keywords

Wishart distributioninference procedures

Mathematics Subject Classification ID

Related Items (6)

Sharp minimax tests for large Toeplitz covariance matrices with repeated observations ⋮ Step-Down diagnostic analysis for monitoring the covariance matrix of bivariate normal processes ⋮ Discriminant analysis in small and large dimensions ⋮ Maximum pairwise Bayes factors for covariance structure testing ⋮ Exact and asymptotic tests on a factor model in low and large dimensions with applications ⋮ Recent advances in shrinkage-based high-dimensional inference

Cites Work

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• On the distribution of the largest eigenvalue in principal components analysis
• Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size
• CLT for linear spectral statistics of large-dimensional sample covariance matrices.
• On some tests of the covariance matrix under general conditions
• On some test criteria for covariance matrix
• Tests for High-Dimensional Covariance Matrices
• Computing the distribution of quadratic forms in normal variables
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