Title
Testing For The Redundancy Of Variables In Principal Components Analysis
Keywords
Asymptotic expansion; Bartlett adjustment factor; dimensionality reduction
Abstract
When all of the important principal components have zero coefficients on the same original variables, then those variables are redundant and may be eliminated. Tyler (1981) derived a statistic suitable for testing such a hypothesis. An asymptotic expansion for the mean of this statistic is obtained and used to calculate a Bartlett adjustment factor. The performances of the unadjusted and adjusted statistics are investigated in a simulation. © 1991.
Publication Date
1-1-1991
Publication Title
Statistics and Probability Letters
Volume
11
Issue
6
Number of Pages
495-501
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/0167-7152(91)90114-7
Copyright Status
Unknown
Socpus ID
44949270805 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/44949270805
STARS Citation
Schott, James R., "Testing For The Redundancy Of Variables In Principal Components Analysis" (1991). Scopus Export 1990s. 1310.
https://stars.library.ucf.edu/scopus1990/1310