Package: bandsfdp
Title: Compute Upper Prediction Bounds on the FDP in Competition-Based
        Setups
Version: 1.1.0
Authors@R: c(
    person("Arya", "Ebadi", , "aeba3842@uni.sydney.edu.au", role = c("aut", "cre")),
    person("Dong", "Luo", , "dluo7139@uni.sydney.edu.au", role = "aut"),
    person("Jack", "Freestone", , "jfre0619@uni.sydney.edu.au", role = "aut"),
    person("William Stafford", "Noble", , "william-noble@uw.edu", role = "aut"),
    person("Uri", "Keich", , "uri.keich@sydney.edu.au", role = "aut",
           comment = c(ORCID = "0000-0002-3209-5011"))
  )
Suggests: fdpbandsdata
Description: 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.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.1.2
URL: https://github.com/uni-Arya/bandsfdp
BugReports: https://github.com/uni-Arya/bandsfdp/issues
NeedsCompilation: no
Packaged: 2023-05-12 06:44:34 UTC; aeba3842
Author: Arya Ebadi [aut, cre],
  Dong Luo [aut],
  Jack Freestone [aut],
  William Stafford Noble [aut],
  Uri Keich [aut] (<https://orcid.org/0000-0002-3209-5011>)
Maintainer: Arya Ebadi <aeba3842@uni.sydney.edu.au>
Repository: CRAN
Date/Publication: 2023-05-12 07:20:03 UTC
Built: R 4.2.0; ; 2023-05-16 21:17:22 UTC; unix
