Package: weightedGCM 0.1.0
weightedGCM: Weighted Generalised Covariance Measure Conditional Independence Test
A conditional independence test that can be applied both to univariate and multivariate random variables. The test is based on a weighted form of the sample covariance of the residuals after a nonlinear regression on the conditioning variables. Details are described in Scheidegger, Hoerrmann and Buehlmann (2021) "The Weighted Generalised Covariance Measure" <arxiv:2111.04361>. The test is a generalisation of the Generalised Covariance Measure (GCM) implemented in the R package 'GeneralisedCovarianceMeasure' by Jonas Peters and Rajen D. Shah based on Shah and Peters (2020) "The Hardness of Conditional Independence Testing and the Generalised Covariance Measure" <arxiv:1804.07203>.
Authors:
weightedGCM_0.1.0.tar.gz
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weightedGCM.pdf |weightedGCM.html✨
weightedGCM/json (API)
NEWS
| # Install 'weightedGCM' in R: |
| install.packages('weightedGCM', repos = c('https://cyrillsch.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:1bc8c0dcee. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 17 2024 |
| R-4.5-win | OK | Nov 17 2024 |
| R-4.5-linux | OK | Nov 17 2024 |
| R-4.4-win | OK | Nov 17 2024 |
| R-4.4-mac | OK | Nov 17 2024 |
| R-4.3-win | OK | Nov 17 2024 |
| R-4.3-mac | OK | Nov 17 2024 |
Dependencies:CVSTdata.tableGeneralisedCovarianceMeasurejsonlitekernlablatticeMatrixmgcvnlmexgboost
