hierbase: Enabling Hierarchical Multiple Testing

Implementation of hierarchical inference based on Meinshausen (2008). Hierarchical testing of variable importance. Biometrika, 95(2), 265-278 and Renaux, Buzdugan, Kalisch, and Bühlmann, (2020). Hierarchical inference for genome-wide association studies: a view on methodology with software. Computational Statistics, 35(1), 1-40. The R-package 'hierbase' offers tools to perform hierarchical inference for one or multiple data sets based on ready-to-use (group) test functions or alternatively a user specified (group) test function. The procedure is based on a hierarchical multiple testing correction and controls the family-wise error rate (FWER). The functions can easily be run in parallel. Hierarchical inference can be applied to (low- or) high-dimensional data sets to find significant groups or single variables (depending on the signal strength and correlation structure) in a data-driven and automated procedure. Possible applications can for example be found in statistical genetics and statistical genomics.

Version: 0.1.2
Depends: R (≥ 4.0.0)
Imports: glmnet, hdi, methods, parallel, stats, SIHR
Suggests: knitr, MASS, testthat
Published: 2021-11-08
Author: Claude Renaux [aut, cre], Peter Bühlmann [ths]
Maintainer: Claude Renaux <renaux at stat.math.ethz.ch>
License: GPL-3
NeedsCompilation: no
Citation: hierbase citation info
Materials: README NEWS
CRAN checks: hierbase results

Documentation:

Reference manual: hierbase.pdf
Vignettes: vignette-hierbase.Rnw

Downloads:

Package source: hierbase_0.1.2.tar.gz
Windows binaries: r-devel: hierbase_0.1.2.zip, r-release: hierbase_0.1.2.zip, r-oldrel: hierbase_0.1.2.zip
macOS binaries: r-release (arm64): hierbase_0.1.2.tgz, r-release (x86_64): hierbase_0.1.2.tgz, r-oldrel: hierbase_0.1.2.tgz
Old sources: hierbase archive

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