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fbroc  

Fast Algorithms to Bootstrap Receiver Operating Characteristics Curves
View on CRAN: Click here


Download and install fbroc package within the R console
Install from CRAN:
install.packages("fbroc")

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

Install by package version:
library("remotes")
install_version("fbroc", "0.4.1")



Attach the package and use:
library("fbroc")
Maintained by
Erik Peter
[Scholar Profile | Author Map]
First Published: 2015-05-05
Latest Update: 2019-03-24
Description:
Implements a very fast C++ algorithm to quickly bootstrap receiver operating characteristics (ROC) curves and derived performance metrics, including the area under the curve (AUC) and the partial area under the curve as well as the true and false positive rate. The analysis of paired receiver operating curves is supported as well, so that a comparison of two predictors is possible. You can also plot the results and calculate confidence intervals. On a typical desktop computer the time needed for the calculation of 100000 bootstrap replicates given 500 observations requires time on the order of magnitude of one second.
How to cite:
Erik Peter (2015). fbroc: Fast Algorithms to Bootstrap Receiver Operating Characteristics Curves. R package version 0.4.1, https://cran.r-project.org/web/packages/fbroc. Accessed 06 Apr. 2025.
Previous versions and publish date:
0.1.0 (2015-05-05 16:14), 0.2.0 (2015-06-06 01:49), 0.2.1 (2015-06-07 08:00), 0.3.0 (2015-10-08 20:13), 0.3.1 (2015-10-12 21:02), 0.4.0 (2016-06-21 22:39)
Other packages that cited fbroc R package
View fbroc citation profile
Other R packages that fbroc depends, imports, suggests or enhances
Complete documentation for fbroc
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