Regularized Generalized Canonical Correlation Analysis: A Framework for Sequential Multiblock Component Methods
Michel Tenenhaus1, Arthur Tenenhaus2,3, Patrick J F Groenen4
1HEC Paris, Jouy-en-Josas, France.
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, [Formula: see text], [Formula: see text] or [Formula: see text] and shrinkage constants 0 or 1, many multiblock component methods are recovered.
Related Concept Videos
Vector Algebra: Method of Components
In many applications, the magnitudes and directions of...
Block Diagram Reduction
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...
Extraction: Partition and Distribution Coefficients
For extracting a solute from an aqueous phase into an...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Relation between Mathematical Equations and Block Diagrams


