ghcm: Functional Conditional Independence Testing with the GHCM

A statistical hypothesis test for conditional independence. Given residuals from a sufficiently powerful regression, it tests whether the covariance of the residuals is vanishing. It can be applied to both discretely-observed functional data and multivariate data. Details of the method can be found in Anton Rask Lundborg, Rajen D. Shah and Jonas Peters (2022) <doi:10.1111/rssb.12544>.

Version:	3.0.1
Depends:	R (≥ 4.0.0)
Imports:	CompQuadForm, Rcpp, splines
LinkingTo:	Rcpp
Suggests:	graphics, stats, utils, refund, testthat, knitr, rmarkdown, bookdown, ggplot2, reshape2, dplyr, tidyr
Published:	2023-11-02
DOI:	10.32614/CRAN.package.ghcm
Author:	Anton Rask Lundborg [aut, cre], Rajen D. Shah [aut], Jonas Peters [aut]
Maintainer:	Anton Rask Lundborg <arl at math.ku.dk>
BugReports:	https://github.com/arlundborg/ghcm/issues
License:	MIT + file LICENSE
URL:	https://github.com/arlundborg/ghcm
NeedsCompilation:	yes
Materials:	README NEWS
CRAN checks:	ghcm results

Documentation:

Reference manual:	ghcm.pdf
Vignettes:	ghcm

Downloads:

Package source:	ghcm_3.0.1.tar.gz
Windows binaries:	r-devel: ghcm_3.0.1.zip, r-release: ghcm_3.0.1.zip, r-oldrel: ghcm_3.0.1.zip
macOS binaries:	r-release (arm64): ghcm_3.0.1.tgz, r-oldrel (arm64): ghcm_3.0.1.tgz, r-release (x86_64): ghcm_3.0.1.tgz, r-oldrel (x86_64): ghcm_3.0.1.tgz
Old sources:	ghcm archive

Linking:

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