Title
Canonical Mean Projections And Confidence Regions In Canonical Variate Analysis
Keywords
Asymptotic covariance of latent vectors; Axis-independent confidence region; Canonical variate subspace; Eigenprojection
Abstract
In developing confidence regions for canonical mean variates, Krzanowski (1989) made use of approximate asymptotic variances and covariances of the elements of the canonical variate coefficient vectors. This procedure is improved upon by the use of the asymptotically correct variances and covariances. However, comparisons of the confidence regions, with and without this improvement, reveal that both perform inadequately if the latent roots corresponding to the canonical variates involved are not well separated. An alternative method based on confidence regions for a canonical mean projection is proposed. The performances of these confidence regions are investigated in a simulation and the method is illustrated by a numerical example. © 1990 Biometrika Trust.
Publication Date
9-1-1990
Publication Title
Biometrika
Volume
77
Issue
3
Number of Pages
587-596
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1093/biomet/77.3.587
Copyright Status
Unknown
Socpus ID
0040708346 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0040708346
STARS Citation
Schott, James R., "Canonical Mean Projections And Confidence Regions In Canonical Variate Analysis" (1990). Scopus Export 1990s. 1501.
https://stars.library.ucf.edu/scopus1990/1501