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-any)SHRED_1.0.0.zip(r-4.6-any)SHRED_1.0.0.zip(r-4.5-any)
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✨
DESCRIPTION
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 298 downloads 11 exports 2 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK91
source / vignettesOK170
linux-releaseOK88
macos-releaseOK167
macos-oldrelOK184
windows-develOK53
windows-releaseOK65
windows-oldrelOK47
wasm-releaseOK78

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

Dependencies:ClustOfVarPCAmixdata