Package: Ckmeans.1d.dp
Type: Package
Version: 4.2.1
Date: 2017-07-07
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: Fast optimal univariate clustering and segementation
 by dynamic programming. Three types of problem including
 univariate k-means, k-median, and k-segments are solved with
 guaranteed optimality and reproducibility. The core algorithm
 minimizes the sum of within-cluster distances using respective
 metrics. Its 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. In contrast to
 heuristic methods, this package provides a powerful set of tools
 for univariate data analysis with guaranteed optimality.
License: LGPL (>= 3)
NeedsCompilation: yes
Suggests: testthat, knitr, rmarkdown
Depends: R (>= 2.10.0)
LazyData: true
VignetteBuilder: knitr
Packaged: 2017-07-08 06:04:27 UTC; joemsong
Repository: CRAN
Date/Publication: 2017-07-09 06:24:02 UTC
