Package: Ckmeans.1d.dp
Type: Package
Version: 3.4.6-5
Date: 2016-12-05
Title: Optimal and Fast Univariate k-Means 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 dynamic programming algorithm for optimal univariate k-means
 clustering. Minimizing the sum of squares of within-cluster distances, the
 algorithm guarantees optimality and reproducibility. Its advantage over
 heuristic clustering algorithms in efficiency and accuracy is increasingly
 pronounced as the number of clusters k increases. With optional weights,
 the algorithm can also analyze 1-D signals for segmentation and peak
 calling. An auxiliary function can generate adaptive histograms to make
 patterns in data stand out. For univariate data analysis, the package
 provides a powerful alternative to heuristic clustering algorithms.
License: LGPL (>= 3)
NeedsCompilation: yes
Suggests: testthat, knitr, rmarkdown
Depends: R (>= 2.10.0)
LazyData: true
VignetteBuilder: knitr
Packaged: 2016-12-05 07:45:19 UTC; joemsong
Repository: CRAN
Date/Publication: 2016-12-05 14:49:19
