A better approximation of moments of the eigenvalues and eigenvectors of the sample covariance matrix

DOI10.1016/j.jmva.2015.08.002zbMath1325.62118OpenAlexW1417528826MaRDI QIDQ893173

A. Enguix-González, Juan M. Muñoz-Pichardo, Juan Luis Moreno-Rebollo

Publication date: 13 November 2015

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

Full work available at URL: https://doi.org/10.1016/j.jmva.2015.08.002

zbMATH Keywords

eigenvaluesprincipal component analysiseigenvectorssample covariance matrixinfluence analysis

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Factor analysis and principal components; correspondence analysis (62H25)

Cites Work

• Using conditional bias in principal component analysis for the evaluation of joint influence on the eigenvalues of the covariance matrix
• TESTS OF SIGNIFICANCE FOR THE LATENT ROOTS OF COVARIANCE AND CORRELATION MATRICES
• On the Sampling Theory of Roots of Determinantal Equations
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