stabs: Stability Selection with Error Control

Resampling procedures to assess the stability of selected variables with additional finite sample error control for high-dimensional variable selection procedures such as Lasso or boosting. Both, standard stability selection (Meinshausen & Buhlmann, 2010, <doi:10.1111/j.1467-9868.2010.00740.x>) and complementary pairs stability selection with improved error bounds (Shah & Samworth, 2013, <doi:10.1111/j.1467-9868.2011.01034.x>) are implemented. The package can be combined with arbitrary user specified variable selection approaches.

Version:	0.6-4
Depends:	R (≥ 2.14.0), methods, stats, parallel
Imports:	graphics, grDevices, utils
Suggests:	glmnet, lars, mboost (> 2.3-0), gamboostLSS (≥ 1.2-0), TH.data, hdi, testthat, knitr, rmarkdown
Published:	2021-01-29
Author:	Benjamin Hofner [aut, cre], Torsten Hothorn [aut]
Maintainer:	Benjamin Hofner <benjamin.hofner at pei.de>
License:	GPL-2
URL:	https://github.com/hofnerb/stabs
NeedsCompilation:	no
Citation:	stabs citation info
Materials:	README NEWS ChangeLog
In views:	MachineLearning
CRAN checks:	stabs results

Documentation:

Reference manual:	stabs.pdf
Vignettes:	Stability selection - Using stabs

Downloads:

Package source:	stabs_0.6-4.tar.gz
Windows binaries:	r-devel: stabs_0.6-4.zip, r-release: stabs_0.6-4.zip, r-oldrel: stabs_0.6-4.zip
macOS binaries:	r-release (arm64): stabs_0.6-4.tgz, r-oldrel (arm64): stabs_0.6-4.tgz, r-release (x86_64): stabs_0.6-4.tgz, r-oldrel (x86_64): stabs_0.6-4.tgz
Old sources:	stabs archive

Reverse dependencies:

Reverse depends:	gamboostLSS, mboost
Reverse imports:	DIFboost, FDboost, MetNet, monaLisa
Reverse suggests:	knockoff

Linking:

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