Title

Asymptotics of eigenprojections of correlation matrices with some applications in principal components analysis

Keywords

Principal component subspace; Rank of asymptotic covariance matrix

Abstract

The asymptotic distribution of an eigenprojection for a sample correlation matrix is obtained. In particular, it is shown that the rank of the asymptotic covariance matrix depends on distributional parameters in a somewhat complicated manner. The results obtained in this paper can be used to determine this rank. Some applications of the asymptotic distribution of these eigenprojections to inferential problems involving principal components subspaces are given.

Publication Date

1-1-1997

Publication Title

Biometrika

Volume

84

Issue

2

Number of Pages

327-337

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1093/biomet/84.2.327

Socpus ID

0007038401 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0007038401

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