knockoff: The Knockoff Filter for Controlled Variable Selection

The knockoff filter is a general procedure for controlling the false discovery rate (FDR) when performing variable selection. For more information, see the website below and the accompanying paper: Candes et al., "Panning for Gold: Model-free Knockoffs for High-dimensional Controlled Variable Selection", 2016, <arXiv:1610.02351>.

Version: 0.3.0
Depends: methods, stats
Imports: Rdsdp, Matrix, corpcor, glmnet, RSpectra, gtools
Suggests: knitr, testthat, rmarkdown, lars, ranger, stabs, flare, doMC, parallel
Published: 2017-10-17
Author: Rina Foygel Barber [ctb] (Development of the original fixed-design Knockoffs), Emmanuel Candes [ctb] (Development of Model-Free Knockoffs and original fixed-design Knockoffs), Lucas Janson [ctb] (Development of Model-Free Knockoffs), Evan Patterson [aut] (Original R package for the original fixed-design Knockoffs), Matteo Sesia [aut, cre] (R package for Model-Free Knockoffs)
Maintainer: Matteo Sesia <msesia at>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
CRAN checks: knockoff results


Reference manual: knockoff.pdf
Vignettes: Advanced Usage of the Knockoff Filter for R
Controlled variable Selection with Fixed-X Knockoffs
Analysis of HIV Drug Resistance Data
Controlled variable Selection with Model-X knockoffs
Package source: knockoff_0.3.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: knockoff_0.3.0.tgz, r-oldrel: knockoff_0.2.1.tgz
Old sources: knockoff archive

Reverse dependencies:

Reverse suggests: CBDA


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