leaderCluster: Leader Clustering Algorithm

The leader clustering algorithm provides a means for clustering a set of data points. Unlike many other clustering algorithms it does not require the user to specify the number of clusters, but instead requires the approximate radius of a cluster as its primary tuning parameter. The package provides a fast implementation of this algorithm in n-dimensions using Lp-distances (with special cases for p=1,2, and infinity) as well as for spatial data using the Haversine formula, which takes latitude/longitude pairs as inputs and clusters based on great circle distances.

Version: 1.5
Published: 2023-03-24
DOI: 10.32614/CRAN.package.leaderCluster
Author: Taylor B. Arnold
Maintainer: Taylor B. Arnold <tarnold2 at richmond.edu>
License: LGPL-2
NeedsCompilation: yes
Materials: README
CRAN checks: leaderCluster results

Documentation:

Reference manual: leaderCluster.pdf

Downloads:

Package source: leaderCluster_1.5.tar.gz
Windows binaries: r-devel: leaderCluster_1.5.zip, r-release: leaderCluster_1.5.zip, r-oldrel: leaderCluster_1.5.zip
macOS binaries: r-release (arm64): leaderCluster_1.5.tgz, r-oldrel (arm64): leaderCluster_1.5.tgz, r-release (x86_64): leaderCluster_1.5.tgz, r-oldrel (x86_64): leaderCluster_1.5.tgz
Old sources: leaderCluster archive

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