Calculates the canonical correlation and canonical covariates.
Examples
data("Russett", package = "RGCCA")
X_agric <- as.matrix(Russett[, c("gini", "farm", "rent")])
X_ind <- as.matrix(Russett[, c("gnpr", "labo")])
X_polit <- as.matrix(Russett[ , c("inst", "ecks", "death", "demostab",
"dictator")])
A <- list(X_agric, X_ind, X_polit)
A <- lapply(A, function(x) scale2(x, bias = TRUE))
C <- matrix(c(0, 0, 1, 0, 0, 1, 1, 1, 0), 3, 3)
out <- RGCCA::rgcca(A, C, tau =rep(0, 3), scheme = "factorial",
scale = FALSE, verbose = FALSE, ncomp = rep(2, length(A)))
out <- improve(out, c("Agric", "Ind", "Polit"))
ccas <- cca_rgcca(out)