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: 0.1.0
Imports: glmnet, randomForest, MASS, stats, RPtests
Suggests: xyz
Published: 2019-10-11
Author: Jana Jankova [aut, cre], Rajen Shah [aut], Peter Buehlmann [aut], Richard Samworth [aut]
Maintainer: Jana Jankova <jana.jankova at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
CRAN checks: GRPtests results

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Reference manual: GRPtests.pdf
Package source: GRPtests_0.1.0.tar.gz
Windows binaries: r-devel: GRPtests_0.1.0.zip, r-devel-gcc8: GRPtests_0.1.0.zip, r-release: GRPtests_0.1.0.zip, r-oldrel: GRPtests_0.1.0.zip
OS X binaries: r-release: GRPtests_0.1.0.tgz, r-oldrel: GRPtests_0.1.0.tgz

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