The goal of RGCCA is to provide Regularized Canonical Correlation Analysis. This fork is for better understanding RGCCA and test the results. It also extends some functionality so that a different design can be used on each dimension.
You can install the released version of RGCCA from CRAN with:
install.packages("RGCCA")And this fork from GitHub with:
# install.packages("devtools")
devtools::install_github("llrs/RGCCA")This is a basic example which shows you how the Agricultural inequality, the industrial development and the political enviroment classify some countries in 1964:
data(Russett)
X_agric =as.matrix(Russett[,c("gini","farm","rent")])
X_ind = as.matrix(Russett[,c("gnpr","labo")])
X_polit = as.matrix(Russett[ , c("demostab", "dictator")])
A = list(X_agric, X_ind, X_polit)
#Define the design matrix (output = C)
C = matrix(c(0, 0, 1, 0, 0, 1, 1, 1, 0), 3, 3)
result.rgcca = rgcca(A, C, tau = c(1, 1, 1), scheme = "factorial", scale = TRUE)
lab = as.vector(apply(Russett[, 9:11], 1, which.max))
plot(result.rgcca$Y[[1]], result.rgcca$Y[[2]], col = "white",
xlab = "Y1 (Agric. inequality)", ylab = "Y2 (Industrial Development)")
text(result.rgcca$Y[[1]], result.rgcca$Y[[2]], rownames(Russett), col = lab, cex = .7)