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stepdownfdp: A Step-Down Procedure to Control the False Discovery Proportion

Provides a step-down procedure for controlling the False Discovery Proportion (FDP) in a competition-based setup, implementing Dong et al. (2020) <doi:10.48550/arXiv.2011.11939>. Such setups include target-decoy competition (TDC) in computational mass spectrometry and the knockoff construction in linear regression.

Version: 1.0.0
Imports: pracma, stats
Published: 2022-03-16
Author: Arya Ebadi [aut, cre], Dong Luo [aut], Kristen Emery [aut], Yilun He [aut], William Stafford Noble [aut], Uri Keich ORCID iD [aut]
Maintainer: Arya Ebadi <aeba3842 at uni.sydney.edu.au>
License: MIT + file LICENSE
URL: https://github.com/uni-Arya/stepdownfdp
NeedsCompilation: no
Materials: README
CRAN checks: stepdownfdp results

Documentation:

Reference manual: stepdownfdp.pdf

Downloads:

Package source: stepdownfdp_1.0.0.tar.gz
Windows binaries: r-devel: stepdownfdp_1.0.0.zip, r-release: stepdownfdp_1.0.0.zip, r-oldrel: stepdownfdp_1.0.0.zip
macOS binaries: r-release (arm64): stepdownfdp_1.0.0.tgz, r-oldrel (arm64): stepdownfdp_1.0.0.tgz, r-release (x86_64): stepdownfdp_1.0.0.tgz, r-oldrel (x86_64): stepdownfdp_1.0.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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