available_methods

<p>List the methods that can be used with the rgcca function.</p>

Multi-block data analysis concerns the analysis of several
sets of variables (blocks) observed on the same group of individuals.
The main aims of the RGCCA package are: to study the relationships
between blocks and to identify subsets of variables of each block
which are active in their relationships with the other blocks. This
package allows to (i) run R/SGCCA and related methods,
(ii) help the user to find out the optimal parameters for R/SGCCA such
as regularization parameters (tau or sparsity), (iii) evaluate the
stability of the RGCCA results and their significance, (iv) build predictive
models from the R/SGCCA. (v) Generic print()
and plot() functions apply to all these functionalities.

Arthur Tenenhaus

RGCCA

Regularized and Sparse Generalized Canonical Correlation
Analysis for Multiblock Data

Fabien Girka

Etienne Camenen

Caroline Peltier

Arnaud Gloaguen

Vincent Guillemot

Laurent Le Brusquet

available_methods function

Available methods for RGCCA — available_methods

Available methods for RGCCA

available_methods: Available methods for RGCCA

Description

Usage

Arguments

Value

Examples