Ckmeans.1d.dp: Optimal k-means clustering for one-dimensional data

This package implements a dynamic programming algorithm to perform optimal one-dimensional k-means clustering, by minimizing the sum of squares of within-cluster distances. As an alternative to the standard heuristic k-means algorithm, this algorithm guarantees optimality and repeatability.

Version: 3.02
Depends: R (≥ 2.10.0)
Published: 2014-03-30
Author: Joe Song and Haizhou Wang
Maintainer: Joe Song <joemsong at cs.nmsu.edu>
License: LGPL (≥ 3)
NeedsCompilation: yes
Citation: Ckmeans.1d.dp citation info
CRAN checks: Ckmeans.1d.dp results

Downloads:

Reference manual: Ckmeans.1d.dp.pdf
Package source: Ckmeans.1d.dp_3.02.tar.gz
Windows binaries: r-devel: Ckmeans.1d.dp_3.02.zip, r-release: Ckmeans.1d.dp_3.02.zip, r-oldrel: Ckmeans.1d.dp_3.02.zip
OS X Snow Leopard binaries: r-release: Ckmeans.1d.dp_3.02.tgz, r-oldrel: Ckmeans.1d.dp_3.02.tgz
OS X Mavericks binaries: r-release: Ckmeans.1d.dp_3.02.tgz
Old sources: Ckmeans.1d.dp archive

Reverse dependencies:

Reverse imports: opm