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 (2021) <arXiv:2101.07108>.
| Version: |
3.0.0 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
graphics, MASS, refund, stats, utils, CompQuadForm, Rcpp, splines |
| LinkingTo: |
Rcpp |
| Suggests: |
testthat, knitr, rmarkdown, bookdown, GeneralisedCovarianceMeasure, ggplot2, reshape2, dplyr, tidyr |
| Published: |
2022-02-20 |
| Author: |
Anton Rask Lundborg [aut, cre],
Rajen D. Shah [aut],
Jonas Peters [aut] |
| Maintainer: |
Anton Rask Lundborg <a.lundborg at statslab.cam.ac.uk> |
| 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:
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