bandsfdp: Compute Upper Prediction Bounds on the FDP in Competition-Based Setups

Implements functions that calculate upper prediction bounds on the false discovery proportion (FDP) in the list of discoveries returned by competition-based setups, implementing Ebadi et al. (2022) <arXiv:2302.11837>. Such setups include target-decoy competition (TDC) in computational mass spectrometry and the knockoff construction in linear regression (note this package typically uses the terminology of TDC). Included is the standardized (TDC-SB) and uniform (TDC-UB) bound on TDC's FDP, and the simultaneous standardized and uniform bands. Requires pre-computed Monte Carlo statistics available at <>. This data can be downloaded by running the command 'devtools::install_github("uni-Arya/fdpbandsdata")' in R and restarting R after installation. The size of this data is roughly 81Mb.

Version: 1.0.0
Suggests: fdpbandsdata
Published: 2023-03-15
Author: Arya Ebadi [aut, cre], Dong Luo [aut], Jack Freestone [aut], William Stafford Noble [aut], Uri Keich ORCID iD [aut]
Maintainer: Arya Ebadi <aeba3842 at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: bandsfdp results


Reference manual: bandsfdp.pdf


Package source: bandsfdp_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): bandsfdp_1.0.0.tgz, r-oldrel (arm64): bandsfdp_1.0.0.tgz, r-release (x86_64): bandsfdp_1.0.0.tgz, r-oldrel (x86_64): bandsfdp_1.0.0.tgz


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