ClusTorus: Prediction and 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: |
0.2.2 |
| Depends: |
R (≥ 3.6.0) |
| Imports: |
BAMBI, igraph, purrr, ggplot2, rlang, stats, utils, cowplot |
| Suggests: |
knitr, rmarkdown, tidyverse |
| Published: |
2022-01-04 |
| DOI: |
10.32614/CRAN.package.ClusTorus |
| 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 |
Documentation:
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