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bandsfdp  

Compute Upper Prediction Bounds on the FDP in Competition-Based Setups
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Download and install bandsfdp package within the R console
Install from CRAN:
install.packages("bandsfdp")

Install from Github:
library("remotes")
install_github("cran/bandsfdp")

Install by package version:
library("remotes")
install_version("bandsfdp", "1.1.0")



Attach the package and use:
library("bandsfdp")
Maintained by
Arya Ebadi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-03-15
Latest Update: 2023-05-12
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) . 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.
How to cite:
Arya Ebadi (2023). bandsfdp: Compute Upper Prediction Bounds on the FDP in Competition-Based Setups. R package version 1.1.0, https://cran.r-project.org/web/packages/bandsfdp. Accessed 30 Jan. 2025.
Previous versions and publish date:
1.0.0 (2023-03-15 19:10)
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Complete documentation for bandsfdp
Functions, R codes and Examples using the bandsfdp R package
Some associated functions: gen_bound . sim_bound . tdc_sb . tdc_ub . 
Some associated R codes: gen_bound.R . onLoad.R . sim_bound.R . tdc_sb.R . tdc_ub.R .  Full bandsfdp package functions and examples
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