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RGCCA (version 2.1.2)

Regularized and Sparse Generalized Canonical Correlation Analysis for Multiblock Data

Description

Multiblock 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: (i) to study the relationships between blocks and (ii) to identify subsets of variables of each block which are active in their relationships with the other blocks.

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Version

Install

install.packages('RGCCA')

Monthly Downloads

501

Version

2.1.2

License

GPL (>= 2)

Maintainer

Arthur Tenenhaus

Last Published

May 11th, 2017

Functions in RGCCA (2.1.2)

miscrossprod

Cross product function for inputs with missing data.
rgcca

Regularized Generalized Canonical Correlation Analysis (RGCCA)
sgcca

Variable Selection For Generalized Canonical Correlation Analysis (SGCCA)
sgccak

Internal function for computing the SGCCA parameters (SGCCA block components, outer weight vectors etc.)
cov2

Variance and Covariance (Matrices)
defl.select

deflation function
rgccak

Internal function for computing the RGCCA parameters (RGCCA block components, outer weight vectors, etc.).
scale2

Scaling and Centering of Matrix-like Objects
BinarySearch

Internal function which does not have to be used by the users
Russett

Russett data
soft

the function soft() encodes the soft-thresholding operator
soft.threshold

The function soft.threshold() soft-thresholds a vector such that the L1-norm constraint is satisfied.
tau.estimate

Optimal shrinkage intensity parameters.