ROC Analysis in Three-Class Classification Problems for
Clustered Data
Duc-Khanh To [aut, cre] (<https://orcid.org/0000-0002-4641-0764>), with contributions from Gianfranco Adimari and Monica Chiogna
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.
R (>= 3.5.0), stats, utils, graphics, nlme
rgl, car, numDeriv, ggplot2, ggpubr, snow, doSNOW, foreach

R (>= 3.5.0), stats, utils, graphics, nlme, Rcpp (>= 0.12.3)
rgl, ellipse, numDeriv, ggplot2, ggpubr, foreach, iterators,
parallel, doParallel

Clustering on the Torus by Conformal Prediction
Provides various tools of for clustering multivariate angular
data on the torus. The package provides angular
adaptations of usual clustering methods such as the k-means
clustering, pairwise angular distances, which can be used as an
input for distance-based clustering algorithms, and implements
clustering based on the conformal prediction framework. Options
for the conformal scores include scores based on a kernel density
estimate, multivariate von Mises mixtures, and naive k-means clusters.
Moreover, the package provides some basic data handling tools for
angular data.
c(person("Sungkyu", "Jung", email = "sungkyu@snu.ac.kr", role = c("aut","cph")),
person("Seungki", "Hong", email = "skgaboja@snu.ac.kr", role = c("aut", "cre")),
person("Kiho", "Park", role = c("ctb")),
person("Byungwon", "Kim", role = c("ctb")))
Sungkyu Jung [aut, cph],
Seungki Hong [aut, cre],
Kiho Park [ctb],
Byungwon Kim [ctb]