variables_contribution: Find variables contributions

In llrs/inteRmodel: Find Models of Interaction

Find variables contributions

Description

Return the specific contribution of each variable for each sample for the first dimension of each block.

Usage

variables_contribution(A, res, scale = TRUE, bias = TRUE)

Arguments

A	The original data.
res	The results of sgcca() or rgcca().
scale	Logical value whether to scale or not the data.
bias	Logical value whether to use bias or not when scaling the data.

Value

A list of matrices with the variables of each block and the value for each sample that helps place the sample on the reduced-dimensional space.

Examples

## Not run: 
# Download the dataset's package at http://biodev.cea.fr/sgcca/.
# --> gliomaData_0.4.tar.gz

require(gliomaData)
data(ge_cgh_locIGR)

A <- ge_cgh_locIGR$multiblocks
Loc <- factor(ge_cgh_locIGR$ylabel)
levels(Loc) <- colnames(ge_cgh_locIGR$multiblocks$y)
C <-  matrix(c(0, 0, 1, 0, 0, 1, 1, 1, 0), 3, 3)
tau = c(1, 1, 0)

# rgcca algorithm using the dual formulation for X1 and X2
# and the dual formulation for X3
A[[3]] = A[[3]][, -3]
# sgcca algorithm
result.sgcca = sgcca(A, C, c1 = c(.071,.2, 1), ncomp = c(1, 1, 1),
                     scheme = "centroid", verbose = FALSE)
weights <- variables_contribution(A, result.sgcca)

## End(Not run)

llrs/inteRmodel documentation built on April 1, 2022, 4:04 p.m.