Regularized Generalized Canonical Correlation Analysis: A Framework for Sequential Multiblock Component Methods

91Citations
Citations of this article
101Readers
Mendeley users who have this article in their library.

Abstract

A new framework for sequential multiblock component methods is presented. This framework relies on a new version of regularized generalized canonical correlation analysis (RGCCA) where various scheme functions and shrinkage constants are considered. Two types of between block connections are considered: blocks are either fully connected or connected to the superblock (concatenation of all blocks). The proposed iterative algorithm is monotone convergent and guarantees obtaining at convergence a stationary point of RGCCA. In some cases, the solution of RGCCA is the first eigenvalue/eigenvector of a certain matrix. For the scheme functions x, | x| , x2 or x4 and shrinkage constants 0 or 1, many multiblock component methods are recovered.

Cite

CITATION STYLE

APA

Tenenhaus, M., Tenenhaus, A., & Groenen, P. J. F. (2017). Regularized Generalized Canonical Correlation Analysis: A Framework for Sequential Multiblock Component Methods. Psychometrika, 82(3), 737–777. https://doi.org/10.1007/s11336-017-9573-x

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free