Package: Ckmeans.1d.dp
Type: Package
Version: 4.2.0
Date: 2017-05-29
Title: Optimal and Fast Univariate Clustering
Authors@R: c(person("Joe", "Song", role = c("aut", "cre"),
		     email = "joemsong@cs.nmsu.edu"),
	      person("Haizhou", "Wang", role = "aut"))
Author: Joe Song [aut, cre], Haizhou Wang [aut]
Maintainer: Joe Song <joemsong@cs.nmsu.edu>
Description: A fast dynamic programming algorithmic framework to
 achieve optimal univariate k-means, k-median, and k-segments
 clustering. Minimizing the sum of respective within-cluster
 distances, the algorithms guarantee optimality and
 reproducibility. Their advantage over heuristic clustering
 algorithms in efficiency and accuracy is increasingly pronounced
 as the number of clusters k increases. Weighted k-means and
 unweighted k-segments algorithms can also optimally segment time
 series and perform peak calling. An auxiliary function generates
 histograms that are adaptive to patterns in data. This package
 provides a powerful alternative to heuristic methods for
 univariate data analysis.
License: LGPL (>= 3)
NeedsCompilation: yes
Suggests: testthat, knitr, rmarkdown
Depends: R (>= 2.10.0)
LazyData: true
VignetteBuilder: knitr
Packaged: 2017-05-30 03:36:19 UTC; joemsong
Repository: CRAN
Date/Publication: 2017-05-30 05:51:09 UTC
