Asymptotic results in canonical discriminant analysis when the dimension is large compared to the sample size

DOI10.1016/j.jspi.2006.09.028zbMath1145.62012OpenAlexW1992768000MaRDI QIDQ947247

Tetsuto Himeno, Hirofumi Wakaki, Yasunori Fujikoshi

Publication date: 29 September 2008

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2006.09.028

zbMATH Keywords

characteristic rootshigh-dimensional frameworkasymptotic null and non-null distributionstests for dimensionality

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Asymptotic distribution theory in statistics (62E20) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (5)

TRUNCATIONS OF HAAR DISTRIBUTED MATRICES, TRACES AND BIVARIATE BROWNIAN BRIDGES ⋮ Statistical inference for functional relationship between the specified and the remainder populations ⋮ Limiting behavior of eigenvalues in high-dimensional MANOVA via RMT ⋮ Asymptotic expansions of test statistics for dimensionality and additional information in canonical correlation analysis when the dimension is large ⋮ High-dimensional linear models: a random matrix perspective

Cites Work

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• TESTS OF SIGNIFICANCE FOR THE LATENT ROOTS OF COVARIANCE AND CORRELATION MATRICES
• TESTS OF SIGNIFICANCE IN CANONICAL ANALYSIS
• Asymptotic Theory for Principal Component Analysis
• On the Limiting Distribution of Roots of a Determinantal Equation

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