GRPtests: Goodness-of-Fit Tests in High-Dimensional GLMs

Methodology for testing nonlinearity in the conditional mean function in low- or high-dimensional generalized linear models, and the significance of (potentially large) groups of predictors. Details on the algorithms can be found in the paper by Jankova, Shah, Buehlmann and Samworth (2019) <arXiv:1908.03606>.

Version: 0.1.2
Imports: glmnet, randomForest, MASS, stats, RPtests, ranger
Suggests: xyz
Published: 2021-03-18
Author: Jana Jankova [aut, cre], Rajen Shah [aut], Peter Buehlmann [aut], Richard Samworth [aut]
Maintainer: Jana Jankova <jana.jankova at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
CRAN checks: GRPtests results


Reference manual: GRPtests.pdf


Package source: GRPtests_0.1.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): GRPtests_0.1.2.tgz, r-release (x86_64): GRPtests_0.1.2.tgz, r-oldrel: GRPtests_0.1.2.tgz
Old sources: GRPtests archive


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