High-dimensional asymptotic expansions for the distributions of canonical correlations

DOI10.1016/j.jmva.2008.04.009zbMath1151.62020OpenAlexW2080517038MaRDI QIDQ958920

Yasunori Fujikoshi, Tetsuro Sakurai

Publication date: 10 December 2008

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

Full work available at URL: https://doi.org/10.1016/j.jmva.2008.04.009

zbMATH Keywords

asymptotic distributionscanonical correlationshigh-dimensional frameworkextended Fisher \(z\)-transformation

Mathematics Subject Classification ID

Related Items (5)

High-Dimensional Edgeworth Expansion of LR Statistic for Testing Circular Symmetric Covariance Structure and Its Error Bound ⋮ Consistency of high-dimensional AIC-type and \(C_p\)-type criteria in multivariate linear regression ⋮ Testing the independence of sets of large-dimensional variables ⋮ Determining the number of canonical correlation pairs for high-dimensional vectors ⋮ A consistency property of the AIC for multivariate linear models when the dimension and the sample size are large

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• Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size
• Testing for complete independence in high dimensions
• Asymptotic expansions for the distributions of the sample roots under nonnormality
• Asymptotic Expansions of the Non-Null Distributions of the Likelihood Ratio Criteria for Multivariate Linear Hypothesis and Independence

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