ClusTorus: 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.

Version: 0.0.1
Depends: R (≥ 3.6.0)
Imports: BAMBI, igraph, purrr, ggplot2, rlang
Suggests: knitr, rmarkdown, tidyverse, cowplot
Published: 2021-02-10
Author: Sungkyu Jung [aut, cph], Seungki Hong [aut, cre], Kiho Park [ctb], Byungwon Kim [ctb]
Maintainer: Seungki Hong <skgaboja at snu.ac.kr>
BugReports: https://github.com/sungkyujung/ClusTorus/issues
License: GPL-3
URL: https://github.com/sungkyujung/ClusTorus
NeedsCompilation: no
CRAN checks: ClusTorus results

Downloads:

Reference manual: ClusTorus.pdf
Vignettes: Introduction to ClusTorus
Package source: ClusTorus_0.0.1.tar.gz
Windows binaries: r-devel: ClusTorus_0.0.1.zip, r-release: ClusTorus_0.0.1.zip, r-oldrel: ClusTorus_0.0.1.zip
macOS binaries: r-release: ClusTorus_0.0.1.tgz, r-oldrel: ClusTorus_0.0.1.tgz

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