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" <doi:10.48550/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" <doi:10.48550/arXiv.1804.07203>.
Version: 0.1.0 Imports: GeneralisedCovarianceMeasure, methods, mgcv, stats, xgboost Suggests: testthat (≥ 3.0.0) Published: 2021-11-29 DOI: 10.32614/CRAN.package.weightedGCM Author: Cyrill Scheidegger [aut, cre], Julia Hoerrmann [ths], Peter Buehlmann [ths], Jonas Peters [ctb, cph] (The code in 'trainFunctions.R' is copied (with small modifications) from the R package 'GeneralisedCovarianceMeasure' by Jonas Peters and Rajen D. Shah), Rajen D. Shah [ctb, cph] (The code in 'trainFunctions.R' is copied (with small modifications) from the R package 'GeneralisedCovarianceMeasure' by Jonas Peters and Rajen D. Shah) Maintainer: Cyrill Scheidegger <cyrill.scheidegger at stat.math.ethz.ch> License: GPL-2 NeedsCompilation: no Materials: README, NEWS CRAN checks: weightedGCM results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=weightedGCM to link to this page.
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