Cluster Analysis Using Thresholding After Random Projections (n-TARP)
Overview
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.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK8 OK2026-03-21
Documentation
- Help pages
- 6
- Examples that run
- 100%4 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 17%
- nTARP Documentation HTML
Downloads
Dependencies
Installing nTARP adds no packages beyond those that come with R.
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- 0.1.0Latest2026-03-20 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-03-20
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 2.4 MB
Cite
Cite this package
Run in R for the authors' entry:
citation("nTARP")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.4231/r74b2zjv.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.