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RGCCA (version 2.0)

RGCCA and Sparse GCCA for multi-block data analysis

Description

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: (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

530

Version

2.0

License

GPL (>= 2)

Maintainer

Arthur Tenenhaus

Last Published

July 24th, 2013

Functions in RGCCA (2.0)

Russett

Russett data
scale2

Scaling and Centering of Matrix-like Objects
soft

the function soft() encodes the soft-thresholding operator
defl.select

deflation function
rgcca

Regularized Generalized Canonical Correlation Analysis (RGCCA)
miscrossprod

Cross product function for inputs with missing data.
cov2

Variance and Covariance (Matrices)
BinarySearch

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

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

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

Optimal shrinkage intensity parameters.