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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 |
Reference manual: | ghcm.pdf |
Vignettes: |
ghcm |
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 |
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