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July, 1981 Asymptotic Inference for Eigenvectors
David E. Tyler
Ann. Statist. 9(4): 725-736 (July, 1981). DOI: 10.1214/aos/1176345514

Abstract

Asymptotic procedures are given for testing certain hypotheses concerning eigenvectors and for constructing confidence regions for eigenvectors. These asymptotic procedures are derived under fairly general conditions on the estimates of the matrix whose eigenvectors are of interest. Applications of the general results to principal components analysis and canonical variate analysis are given.

Citation

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David E. Tyler. "Asymptotic Inference for Eigenvectors." Ann. Statist. 9 (4) 725 - 736, July, 1981. https://doi.org/10.1214/aos/1176345514

Information

Published: July, 1981
First available in Project Euclid: 12 April 2007

zbMATH: 0474.62051
MathSciNet: MR619278
Digital Object Identifier: 10.1214/aos/1176345514

Subjects:
Primary: 62H15
Secondary: 62E20 , 62H20 , 62H25

Keywords: canonical variate analysis , eigenprojections , eigenvectors , elliptical distributions , generalized inverses and asymptotic chi-square statistics , principal components analysis

Rights: Copyright © 1981 Institute of Mathematical Statistics

Vol.9 • No. 4 • July, 1981
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