Compute Upper Prediction Bounds on the FDP in Competition-Based Setups R package bandsfdp version 1.1.0 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 <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. Software Suggests: fdpbandsdata Arya Ebadi <aeba3842@uni.sydney.edu.au> Comprehensive R Archive Network (CRAN) Arya Ebadi [aut, cre], Dong Luo [aut], Jack Freestone [aut], William Stafford Noble [aut], Uri Keich [aut] (ORCID: <https://orcid.org/0000-0002-3209-5011>) MIT + file LICENSE (https://CRAN.R-project.org/package=bandsfdp/LICENSE) 2023-05-12 application/tgz https://CRAN.R-project.org/package=bandsfdp doi:10.32614/CRAN.package.bandsfdp