clusterability: Performs Tests for Cluster Tendency of a Data Set

Test for cluster tendency (clusterability) of a data set. The methods implemented - reducing the data set to a single dimension using principal component analysis or computing pairwise distances, and performing a multimodality test like the Dip Test or Silverman's Critical Bandwidth Test - are described in Adolfsson, Ackerman, and Brownstein (2019) <doi:10.1016/j.patcog.2018.10.026>. Such methods can inform whether clustering algorithms are appropriate for a data set.

Version: 0.1.1.0
Depends: R (≥ 3.4.0)
Imports: diptest, splines
Suggests: testthat
Published: 2020-03-04
Author: Zachariah Neville [aut, cre], Naomi Brownstein [aut], Maya Ackerman [aut], Andreas Adolfsson [aut]
Maintainer: Zachariah Neville <z.neville at stat.fsu.edu>
License: GPL-2
NeedsCompilation: no
Materials: README NEWS
CRAN checks: clusterability results

Documentation:

Reference manual: clusterability.pdf

Downloads:

Package source: clusterability_0.1.1.0.tar.gz
Windows binaries: r-devel: clusterability_0.1.1.0.zip, r-release: clusterability_0.1.1.0.zip, r-oldrel: clusterability_0.1.1.0.zip
macOS binaries: r-release (arm64): clusterability_0.1.1.0.tgz, r-oldrel (arm64): clusterability_0.1.1.0.tgz, r-release (x86_64): clusterability_0.1.1.0.tgz
Old sources: clusterability archive

Reverse dependencies:

Reverse suggests: FCPS

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