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ClusROC: ROC Analysis in Three-Class Classification Problems for Clustered Data

Statistical methods for ROC surface analysis in three-class classification problems for clustered data and in presence of covariates. In particular, the package allows to obtain covariate-specific point and interval estimation for: (i) true class fractions (TCFs) at fixed pairs of thresholds; (ii) the ROC surface; (iii) the volume under ROC surface (VUS); (iv) the optimal pairs of thresholds. Methods considered in points (i), (ii) and (iv) are proposed and discussed in To et al. (2022) <doi:10.1177/09622802221089029>. Referring to point (iv), three different selection criteria are implemented: Generalized Youden Index (GYI), Closest to Perfection (CtP) and Maximum Volume (MV). Methods considered in point (iii) are proposed and discussed in Xiong et al. (2018) <doi:10.1177/0962280217742539>. Visualization tools are also provided. We refer readers to the articles cited above for all details.

Version: 1.0.2
Depends: R (≥ 3.5.0), stats, utils, graphics, nlme, Rcpp (≥ 0.12.3)
Imports: rgl, ellipse, numDeriv, ggplot2, ggpubr, foreach, iterators, parallel, doParallel
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (≥ 3.0.0)
Published: 2022-11-17
DOI: 10.32614/CRAN.package.ClusROC
Author: Duc-Khanh To [aut, cre] (<https://orcid.org/0000-0002-4641-0764>), with contributions from Gianfranco Adimari and Monica Chiogna
Maintainer: Duc-Khanh To <toduc at stat.unipd.it>
BugReports: https://github.com/toduckhanh/ClusROC/issues
License: GPL-3
URL: https://github.com/toduckhanh/ClusROC
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: ClusROC results

Documentation:

Reference manual: ClusROC.pdf

Downloads:

Package source: ClusROC_1.0.2.tar.gz
Windows binaries: r-devel: ClusROC_1.0.2.zip, r-release: ClusROC_1.0.2.zip, r-oldrel: ClusROC_1.0.2.zip
macOS binaries: r-release (arm64): ClusROC_1.0.2.tgz, r-oldrel (arm64): ClusROC_1.0.2.tgz, r-release (x86_64): ClusROC_1.0.2.tgz, r-oldrel (x86_64): ClusROC_1.0.2.tgz
Old sources: ClusROC archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ClusROC 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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