Package: nTARP 0.1.0

David Reeping

nTARP: Cluster Analysis Using Thresholding After Random Projections (n-TARP)

Implements the high-dimensional clustering technique Thresholding After Random Projections (n-TARP). Provides functionality to iteratively decompose larger datasets using contextual variables or within-cluster sum of squares. See Tarun & Boutin (2018) <doi:10.48550/arXiv.1806.05297> and Tarun & Boutin (2018) <doi:10.4231/R74B2ZJV> for the original method and applications.

Authors:David Reeping [aut, cre], Yunmeng Han [aut], Nahal Rashedi [rev]

nTARP_0.1.0.tar.gz
nTARP_0.1.0.tar.gz(r-4.7-any)nTARP_0.1.0.tar.gz(r-4.6-any)
nTARP_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
nTARP/json (API)

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 160 downloads 4 exports 0 dependencies

Last updated from:6499eb7184. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK124
source / vignettesOK217
linux-release-x86_64OK149
wasm-releaseOK95

Exports:build_solution_from_labeled_clustersconsolidate_clustersnTARPnTARP_bisecting

Dependencies:

The nTARP Package

David Reeping

Rendered fromnTARP_documentation.Rmdusingknitr::rmarkdownon May 19 2026.

Last update: 2026-03-20
Started: 2026-03-20