cdcsis

Conditional Distance Correlation Based Feature Screening and Conditional Independence Inference

Conditional distance correlation <doi:10.1080/01621459.2014.993081> is a novel conditional dependence measurement of two multivariate random variables given a confounding variable. This package provides conditional distance correlation, performs the conditional distance correlation sure independence screening procedure for ultrahigh dimensional data <doi:10.5705/ss.202014.0117>, and conducts conditional distance covariance test for conditional independence assumption of two multivariate variable.

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Description file content

Package
cdcsis
Type
Package
Title
Conditional Distance Correlation Based Feature Screening and Conditional Independence Inference
Description
Conditional distance correlation is a novel conditional dependence measurement of two multivariate random variables given a confounding variable. This package provides conditional distance correlation, performs the conditional distance correlation sure independence screening procedure for ultrahigh dimensional data , and conducts conditional distance covariance test for conditional independence assumption of two multivariate variable.
Version
2.0.0
Date
2019-1-3
Author
Wenhao Hu, Mian Huang, Wenliang Pan, Xueqin Wang, Canhong Wen, Yuan Tian, Heping Zhang, Jin Zhu
Depends
R(>= 3.0.1)
Imports
ks, mvtnorm, Rcpp
Suggests
testthat
Maintainer
Jin Zhu
License
GPL (>= 2)
NeedsCompilation
yes
Encoding
UTF-8
RoxygenNote
6.1.1
LinkingTo
Rcpp
URL
BugReports
https://github.com/Mamba413/cdcsis/issues
Packaged
2019-01-04 02:10:59 UTC; JinZhu
Repository
CRAN
Date/Publication
2019-01-09 15:20:19 UTC

install.packages('cdcsis')

2.0.0

12 days ago

https://github.com/Mamba413/cdcsis

Jin Zhu

GPL (>= 2)

Depends on

R(>= 3.0.1)

Imports

ks, mvtnorm, Rcpp

Suggests

testthat

Discussions