jdcov-package: Tests for joint independence via joint distance covariance
In shubhadeep4/jdcov: Tests for joint independence via joint distance covariance

Description Details Author(s) References See Also

Computes joint distance covariance (JdCov) among more than two random vectors of arbitrary dimensions (see Chakraborty and Zhang, 2019) and implements a bootstrap based test for joint independence among the random vectors based on JdCov.

The DESCRIPTION file: This package was not yet installed at build time.

Index: This package was not yet installed at build time.
~~ An overview of how to use the package, including the most important functions ~~

as.person(c("Shubhadeep Chakraborty <shubhadeep_stat@yahoo.in> [aut, cre]","Dongbang Yuan <yuandb@stat.tamu.edu> [aut, cre]", "Xianyang Zhang <zhangxiany@stat.tamu.edu> [aut]"))

Maintainer: Shubhadeep Chakraborty <shubhadeep_stat@yahoo.in>

Chakraborty, S. and Zhang, X. (2019). Distance Metrics for Measuring Joint Dependence with Application to Causal Inference, Journal of the American Statistical Association, DOI: 10.1080/01621459.2018.1513364.

~~ Optional links to other man pages, e.g. ~~ ~~ <pkg> ~~

shubhadeep4/jdcov documentation built on June 4, 2019, 3 a.m.