A test for independence of two sets of variables when the number of variables is large relative to the sample size

DOI10.1016/J.SPL.2008.05.031zbMath1148.62041OpenAlexW2013928517MaRDI QIDQ956401

James R. Schott

Publication date: 25 November 2008

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2008.05.031

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic distribution theory in statistics (62E20) Hypothesis testing in multivariate analysis (62H15)

Related Items (3)

Some correlation tests for vectors of large dimension ⋮ Nonparametric tests of independence based on interpoint distances ⋮ Tests of zero correlation using modified RV coefficient for high-dimensional vectors

Cites Work

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• A test for the mean vector with fewer observations than the dimension
• Dependent unit vectors
• Testing for complete independence in high dimensions
• Some results on the distribution of Wilks's likelihood-ratio criterion
• Exact distributions of Wilks's likelihood ratio criterion
• Asymptotic Expansions for the Moments of the Distribution of Correlation Coefficient
• On the exact distribution of Wilks's criterion
• A GENERAL DISTRIBUTION THEORY FOR A CLASS OF LIKELIHOOD CRITERIA

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