Title

A Test For A Specific Principal Component Of A Correlation Matrix

Keywords

Latent vector; M estimate of scatter

Abstract

In the application of principal components analysis it is common to replace an observed sample principal component vector by another vector closely resembling the sample vector but which is easier to use or interpret. A useful test of hypothesis in this case is one that specifies the true ith principal component. In this article we obtain an asymptotically chi-squared procedure suitable for testing such a hypothesis when the principal components analysis is performed on a correlation matrix. The procedure easily extends to a principal components analysis based on M estimates of scatter. © 1991 Taylor & Francis Group, LLC.

Publication Date

1-1-1991

Publication Title

Journal of the American Statistical Association

Volume

86

Issue

415

Number of Pages

747-751

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1080/01621459.1991.10475104

Socpus ID

0040999451 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0040999451

This document is currently not available here.

Share

COinS