cdcsis-package {cdcsis}R Documentation

Conditional Distance Correlation Based Feature Screening and Conditional Independence Inference

Description

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.

Author(s)

Wenhao Hu, Mian Huang, Wenliang Pan, Xueqin Wang, Canhong Wen, Yuan Tian, Heping Zhang, Jin Zhu Maintainer: Jin Zhu <zhuj37@mail2.sysu.edu.cn>

References

Wang, X., Pan, W., Hu, W., Tian, Y. and Zhang, H., 2015. Conditional distance correlation. Journal of the American Statistical Association, 110(512), pp.1726-1734.

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


[Package cdcsis version 2.0.3 Index]