Package: SHRED 1.0.0

SHRED: Setwise Hierarchical Rate of Erroneous Discovery

Setwise Hierarchical Rate of Erroneous Discovery (SHRED) methods for setwise variable selection with false discovery rate (FDR) control. Setwise variable selection means that sets of variables may be selected when the true variable cannot be identified. This allows us to maintain FDR control but increase power. Details of the SHRED methods are in Organ, Kenney & Gu (2026) <doi:10.48550/arXiv.2603.02160>.

Authors:Sarah Organ [aut], Toby Kenney [cre], Hong Gu [aut]

SHRED_1.0.0.tar.gz
SHRED_1.0.0.zip(r-4.7)SHRED_1.0.0.zip(r-4.6)SHRED_1.0.0.zip(r-4.5)
SHRED_1.0.0.tgz(r-4.6-any)SHRED_1.0.0.tgz(r-4.5-any)
SHRED_1.0.0.tar.gz(r-4.7-any)SHRED_1.0.0.tar.gz(r-4.6-any)
SHRED_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
SHRED/json (API)

# Install 'SHRED' in R:
install.packages('SHRED', repos = c('https://tjk23.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 451 downloads 11 exports 2 dependencies

Last updated from:042f26f0e1. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK97
source / vignettesOK143
linux-release-x86_64OK86
macos-release-arm64OK158
macos-oldrel-arm64OK169
windows-develOK80
windows-releaseOK66
windows-oldrelOK89
wasm-releaseOK92

Exports:convert.to.matrixCumMinWeightsget.p.valsHGLSUPplot.SHREDPRDS.cutoffprint.SHREDSHREDSHRED.cutoffSHREDDERSHREDDER.cutoff

Dependencies:ClustOfVarPCAmixdata