| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 415718 | Computational Statistics & Data Analysis | 2006 | 13 Pages |
Abstract
A set of tools for analyzing relationships between and within multiple data matrices is presented. The starting point is a new, unified approach bridging two existing methods; Carroll's Generalized Canonical Analysis (GCA) with the Tucker-1 method for principal component analysis of multiple matrices. GCA and Tucker-1 are shown to correspond to particular choices of a ridge parameter. The unified method is then generalized to a larger space of methods.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Tobias Dahl, Tormod Næs,