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Fit linear and logistic regression models penalised with group-adaptive elastic net penalties. The group penalties correspond to groups of covariates defined by a co-data group set. The method accommodates inclusion of unpenalised covariates and overlapping groups. See Van Nee et al. (2021) <doi:10.48550/arXiv.2101.03875>.
Version: | 1.1-1 |
Depends: | R (≥ 3.5.0) |
Imports: | glmnet, stats, Matrix, multiridge (≥ 1.5), mvtnorm |
Suggests: | ggplot2, ecpc |
Published: | 2022-05-13 |
DOI: | 10.32614/CRAN.package.squeezy |
Author: | Mirrelijn M. van Nee [aut, cre], Tim van de Brug [aut], Mark A. van de Wiel [aut] |
Maintainer: | Mirrelijn M. van Nee <m.vannee at amsterdamumc.nl> |
License: | GPL (≥ 3) |
URL: | https://arxiv.org/abs/2101.03875 |
NeedsCompilation: | no |
CRAN checks: | squeezy results |
Reference manual: | squeezy.pdf |
Package source: | squeezy_1.1-1.tar.gz |
Windows binaries: | r-devel: squeezy_1.1-1.zip, r-release: squeezy_1.1-1.zip, r-oldrel: squeezy_1.1-1.zip |
macOS binaries: | r-release (arm64): squeezy_1.1-1.tgz, r-oldrel (arm64): squeezy_1.1-1.tgz, r-release (x86_64): squeezy_1.1-1.tgz, r-oldrel (x86_64): squeezy_1.1-1.tgz |
Old sources: | squeezy archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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