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AROC: Covariate-Adjusted Receiver Operating Characteristic Curve Inference

Estimates the covariate-adjusted Receiver Operating Characteristic (AROC) curve and pooled (unadjusted) ROC curve by different methods. Inacio de Carvalho, V., and Rodriguez-Alvarez, M. X. (2018) <doi:10.48550/arXiv.1806.00473>. NOTE: We have created a new package, 'ROCnReg', with more functionalities. It also implements all the methods included in 'AROC'. We, therefore, recommend using 'ROCnReg' ('AROC' will no longer be maintained).

Version: 1.0-4
Imports: stats, grDevices, graphics, splines, np, Matrix, Hmisc, MASS, moments, nor1mix, spatstat.geom
Published: 2022-02-21
Author: Maria Xose Rodriguez-Alvarez ORCID iD [aut, cre], Vanda Inacio ORCID iD [aut]
Maintainer: Maria Xose Rodriguez-Alvarez <mxrodriguez at uvigo.es>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
CRAN checks: AROC results

Documentation:

Reference manual: AROC.pdf

Downloads:

Package source: AROC_1.0-4.tar.gz
Windows binaries: r-devel: AROC_1.0-4.zip, r-release: AROC_1.0-4.zip, r-oldrel: AROC_1.0-4.zip
macOS binaries: r-release (arm64): AROC_1.0-4.tgz, r-oldrel (arm64): AROC_1.0-4.tgz, r-release (x86_64): AROC_1.0-4.tgz, r-oldrel (x86_64): AROC_1.0-4.tgz
Old sources: AROC archive

Reverse dependencies:

Reverse imports: multisite.accuracy

Linking:

Please use the canonical form https://CRAN.R-project.org/package=AROC to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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