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 + fileLICENSE |
| URL: | https://github.com/arlundborg/ghcm |
| NeedsCompilation: | yes |
| Materials: | README,NEWS |
| CRAN checks: | ghcm results |
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