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: 0.6-2
Depends: R (≥ 2.14.0), methods, stats, parallel
Imports: graphics, grDevices, utils
Suggests: glmnet, lars, mboost (> 2.3-0), gamboostLSS (≥ 1.2-0), QUIC, TH.data, hdi, testthat, knitr, rmarkdown, igraph, huge
Published: 2017-01-31
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

Downloads:

Reference manual: stabs.pdf
Vignettes: Stability selection - Using stabs
Graphical networks with stabs
Package source: stabs_0.6-2.tar.gz
Windows binaries: r-devel: stabs_0.6-2.zip, r-release: stabs_0.6-2.zip, r-oldrel: stabs_0.6-2.zip
OS X El Capitan binaries: r-release: stabs_0.6-2.tgz
OS X Mavericks binaries: r-oldrel: stabs_0.6-2.tgz
Old sources: stabs archive

Reverse dependencies:

Reverse depends: mboost
Reverse imports: DIFboost, FDboost

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