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T4cluster: Tools for Cluster Analysis

Cluster analysis is one of the most fundamental problems in data science. We provide a variety of algorithms from clustering to the learning on the space of partitions. See Hennig, Meila, and Rocci (2016, ISBN:9781466551886) for general exposition to cluster analysis.

Version: 0.1.2
Depends: R (≥ 2.10)
Imports: Rcpp (≥ 1.0.5), Rdpack, Rdimtools, ADMM, MASS, fda, ggplot2, lpSolve, maotai, mclustcomp, rstiefel, scatterplot3d, stats, utils
LinkingTo: Rcpp, RcppArmadillo
Published: 2021-08-16
Author: Kisung You ORCID iD [aut, cre]
Maintainer: Kisung You <kisungyou at outlook.com>
BugReports: https://github.com/kisungyou/T4cluster/issues
License: MIT + file LICENSE
URL: https://kisungyou.com/T4cluster/
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: T4cluster results

Documentation:

Reference manual: T4cluster.pdf

Downloads:

Package source: T4cluster_0.1.2.tar.gz
Windows binaries: r-devel: T4cluster_0.1.2.zip, r-release: T4cluster_0.1.2.zip, r-oldrel: T4cluster_0.1.2.zip
macOS binaries: r-release (arm64): T4cluster_0.1.2.tgz, r-oldrel (arm64): T4cluster_0.1.2.tgz, r-release (x86_64): T4cluster_0.1.2.tgz, r-oldrel (x86_64): T4cluster_0.1.2.tgz
Old sources: T4cluster archive

Reverse dependencies:

Reverse imports: Riemann, TDAkit

Linking:

Please use the canonical form https://CRAN.R-project.org/package=T4cluster 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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