Package: oneclust 0.3.0

oneclust: Maximum Homogeneity Clustering for Univariate Data

Maximum homogeneity clustering algorithm for one-dimensional data described in W. D. Fisher (1958) <doi:10.1080/01621459.1958.10501479> via dynamic programming.

Authors:Nan Xiao [aut, cre]

oneclust_0.3.0.tar.gz
oneclust_0.3.0.zip(r-4.7)oneclust_0.3.0.zip(r-4.6)oneclust_0.3.0.zip(r-4.5)
oneclust_0.3.0.tgz(r-4.6-x86_64)oneclust_0.3.0.tgz(r-4.6-arm64)oneclust_0.3.0.tgz(r-4.5-x86_64)oneclust_0.3.0.tgz(r-4.5-arm64)
oneclust_0.3.0.tar.gz(r-4.7-arm64)oneclust_0.3.0.tar.gz(r-4.7-x86_64)oneclust_0.3.0.tar.gz(r-4.6-arm64)oneclust_0.3.0.tar.gz(r-4.6-x86_64)
oneclust_0.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
oneclust/json (API)
NEWS

# Install 'oneclust' in R:
install.packages('oneclust', repos = c('https://nanxstats.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nanxstats/oneclust/issues

Pkgdown/docs site:https://nanx.me

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

clustering-algorithmfeature-engineeringhomogeneitypeak-callingunivariate-datacpp

4.40 score 5 stars 2 scripts 184 downloads 4 exports 1 dependencies

Last updated from:121505b164. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK113
linux-devel-x86_64OK102
source / vignettesOK211
linux-release-arm64OK110
linux-release-x86_64OK109
macos-release-arm64OK76
macos-release-x86_64OK179
macos-oldrel-arm64OK82
macos-oldrel-x86_64OK219
windows-develOK95
windows-releaseOK132
windows-oldrelOK99
wasm-releaseOK98

Exports:cudoneclustsim_postcode_levelssim_postcode_samples

Dependencies:Rcpp

Maximum Homogeneity Clustering for One-Dimensional Data

Nan Xiao <https://nanx.me>

Rendered fromoneclust.Rmdusingknitr::rmarkdownon May 26 2026.

Last update: 2024-03-11
Started: 2020-08-17