MFKnockoffs: Model-Free Knockoff Filter for Controlled Variable Selection

Model-free knockoffs are 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: 0.9.1
Depends: methods, stats
Imports: Rdsdp, Matrix, corpcor, glmnet, RSpectra, gtools
Suggests: knitr, testthat, rmarkdown, lars, ranger, stabs, flare, doMC, parallel
Published: 2017-09-29
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: MFKnockoffs results


Reference manual: MFKnockoffs.pdf
Vignettes: Using the Model-Free Knockoff Filter
Advanced Usage of the Model-Free Knockoff Filter
Using the Knockoff Filter with a Fixed Design Matrix
Package source: MFKnockoffs_0.9.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: MFKnockoffs_0.9.1.tgz
OS X Mavericks binaries: r-oldrel: MFKnockoffs_0.9.1.tgz
Old sources: MFKnockoffs archive


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