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auRoc  

Various Methods to Estimate the AUC
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("auRoc", "0.2-1")



Attach the package and use:
library("auRoc")
Maintained by
Dai Feng
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-12-21
Latest Update: 2020-04-04
Description:
Estimate the AUC using a variety of methods as follows: (1) frequentist nonparametric methods based on the Mann-Whitney statistic or kernel methods. (2) frequentist parametric methods using the likelihood ratio test based on higher-order asymptotic results, the signed log-likelihood ratio test, the Wald test, or the approximate ''t'' solution to the Behrens-Fisher problem. (3) Bayesian parametric MCMC methods.
How to cite:
Dai Feng (2015). auRoc: Various Methods to Estimate the AUC. R package version 0.2-1, https://cran.r-project.org/web/packages/auRoc. Accessed 26 Aug. 2026.
Previous versions and publish date:
(2026-07-09 07:19), 0.1-0 (2015-12-21 21:57), 0.2-0 (2019-01-13 22:10)
Other packages that cited auRoc R package
View auRoc citation profile
Other R packages that auRoc depends, imports, suggests or enhances
Complete documentation for auRoc
Functions, R codes and Examples using the auRoc R package
Some associated functions: auc.nonpara.kernel . auc.nonpara.mw . auc.para.bayes . auc.para.frequentist . petBrainGlioma . 
Some associated R codes: auc.nonpara.kernel.R . auc.nonpara.mw.R . auc.para.bayes.R . auc.para.frequentist.R .  Full auRoc package functions and examples
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