Nothing
library(pbdDEMO, quietly=TRUE)
init.grid()
# "read" in the data
n <- 1e4
p <- 250
comm.set.seed(1234, diff=T)
dx <- ddmatrix("rnorm", nrow=n, ncol=p, bldim=c(4,4), mean=100, sd=25)
# PCA with scaling, retaining only 90% of the variation
pca <- prcomp(x=dx, retx=TRUE, scale=TRUE)
prop_var <- cumsum(pca$sdev)/sum(pca$sdev)
i <- max(min(which(prop_var > 0.9)) - 1, 1)
new_dx <- pca$x[, 1:i]
print(new_dx)
comm.cat("\nNumber of columns retained:\t", i, "\n", quiet=T)
comm.cat("Percentage of columns retained:", i/dim(dx)[2], "\n\n", quiet=T)
finalize()
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