Description Usage Arguments Value Author(s) References See Also Examples
Performs conditional distance correlation sure independence screening (CDC-SIS).
1 2 |
x |
a numeric matrix, or a list which contains multiple numeric matrix |
y |
a numeric vector, matrix, or |
z |
|
width |
a user-specified positive value (univariate conditional variable) or vector (multivariate conditional variable) for
gaussian kernel bandwidth. Its default value is relies on |
threshold |
the threshold of the number of predictors recuited by CDC-SIS.
Should be less than or equal than the number of column of |
distance |
if |
index |
exponent on Euclidean distance, in (0,2] |
num.threads |
number of threads. Default |
ix |
the vector of indices selected by CDC-SIS |
cdcor |
the conditional distance correlation for each univariate/multivariate variable in |
Canhong Wen, Wenliang Pan, Mian Huang, and Xueqin Wang
Wen, C., Pan, W., Huang, M. and Wang, X., 2018. Sure independence screening adjusted for confounding covariates with ultrahigh-dimensional data. Statistica Sinica, 28, pp.293-317. URL http://www3.stat.sinica.edu.tw/statistica/J28N1/28-1.html
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | ## Not run:
library(cdcsis)
########## univariate explanative variables ##########
set.seed(1)
num <- 100
p <- 150
x <- matrix(rnorm(num * p), nrow = num)
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)
########## multivariate explanative variables ##########
x <- as.list(as.data.frame(x))
x <- lapply(x, as.matrix)
x[[1]] <- cbind(x[[1]], x[[2]])
x[[2]] <- NULL
res <- cdcsis(x, y, z)
head(res[["ix"]], n = 10)
########## multivariate response variables ##########
num <- 100
p <- 150
x <- matrix(rnorm(num * p), nrow = num)
z <- rnorm(num)
y1 <- 3 * x[, 1] + 5 * z * x[, 4] + rnorm(num)
y2 <- 3 * x[, 2] + 5 * x[, 3] + 2 * z + rnorm(num)
y <- cbind(y1, y2)
res <- cdcsis(x, y, z)
head(res[["ix"]], n = 10)
## End(Not run)
|
** cdcsis
** - Conditional Feature Screening & Conditional Independence Test.
** Version : 2.0.3 (2021)
** Maintainer : Jin Zhu (zhuj37@mail2.sysu.edu.cn)
**
** Please share any bugs or suggestions to the maintainer.
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