Jin Zhu
You can install the released version of cdcsis from CRAN with:
This is a basic example which shows you how to pick out the important feature from high-dimensional dataset:
library(cdcsis)
set.seed(1)
num <- 100
p <- 1000
x <- matrix(rnorm(num * p), nrow = num, ncol = p)
z <- rnorm(num)
y <- 3*x[, 1] + 1.5*x[, 2] + 4*z*x[, 5] + rnorm(num)
res <- cdcsis(x, y, z)
head(res[["ix"]], n = 10)cdcsis function successfully selects the informative variables from 1000 features pool.
GPL (>= 2)