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, .

Maintainer: Matteo Sesia <msesia at stanford.edu>

Author(s): Rina Foygel Barber* (Development of the original fixed-design Knockoffs), Emmanuel Candes* (Development of Model-Free Knockoffs and original fixed-design Knockoffs), Lucas Janson* (Development of Model-Free Knockoffs), Evan Patterson* (Original R package for the original fixed-design Knockoffs), Matteo Sesia* (R package for Model-Free Knockoffs)

Install package and any missing dependencies by running this line in your R console:

install.packages("knockoff")

Depends methods, stats
Imports Rdsdp, Matrix, corpcor, glmnet, RSpectra, gtools
Suggests knitr, testthat, rmarkdown, lars, ranger, stabs, flare, doMC, parallel
Enhances
Linking to
Reverse
depends
Reverse
imports
Reverse
suggests
Reverse
enhances
Reverse
linking to

Package knockoff
Materials
URL https://web.stanford.edu/group/candes/knockoffs/index.html
Task Views
Version 0.3.0
Published 2017-10-17
License GPL-3
BugReports
SystemRequirements
NeedsCompilation no
Citation
CRAN checks knockoff check results
Package source knockoff_0.3.0.tar.gz