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) <doi:10.48550/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 <https://github.com/uni-Arya/fdpbandsdata>. 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:	1.1.0
Suggests:	fdpbandsdata
Published:	2023-05-12
Author:	Arya Ebadi [aut, cre], Dong Luo [aut], Jack Freestone [aut], William Stafford Noble [aut], Uri Keich [aut]
Maintainer:	Arya Ebadi <aeba3842 at uni.sydney.edu.au>
BugReports:	https://github.com/uni-Arya/bandsfdp/issues
License:	MIT + file LICENSE
URL:	https://github.com/uni-Arya/bandsfdp
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	bandsfdp results

Documentation:

Reference manual:

bandsfdp.pdf

Downloads:

Package source:	bandsfdp_1.1.0.tar.gz
Windows binaries:	r-devel: bandsfdp_1.1.0.zip, r-release: bandsfdp_1.1.0.zip, r-oldrel: bandsfdp_1.1.0.zip
macOS binaries:	r-release (arm64): bandsfdp_1.1.0.tgz, r-oldrel (arm64): bandsfdp_1.1.0.tgz, r-release (x86_64): bandsfdp_1.1.0.tgz, r-oldrel (x86_64): bandsfdp_1.1.0.tgz
Old sources:	bandsfdp archive

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