Package: OptCirClust
Type: Package
Title: Circular, Periodic, or Framed Data Clustering: Fast, Optimal,
        and Reproducible
Version: 0.0.2
Date: 2020-12-12
Authors@R: c(person("Tathagata", "Debnath", role = "aut", 
	                  comment = c(ORCID = "0000-0001-6445-275X")),
             person("Joe", "Song", role = c("aut", "cre"),
                    comment = c(ORCID = "0000-0002-6883-6547"),
		                email = "joemsong@cs.nmsu.edu"))
Author: Tathagata Debnath [aut] (<https://orcid.org/0000-0001-6445-275X>),
  Joe Song [aut, cre] (<https://orcid.org/0000-0002-6883-6547>)
Maintainer: Joe Song <joemsong@cs.nmsu.edu>
Description: Fast, optimal, and reproducible clustering algorithms for
 circular, periodic, or framed data. The algorithms introduced in this
 package are based on a core optimal framed clustering algorithm. The
 runtime of these algorithms is O(K N log^2 N), where K is the number
 of clusters and N is the number of circular data points. On a desktop
 computer using a single processor core, millions of circular data
 points can be clustered within seconds. One can use the algorithms to
 characterize events along circular DNA molecules, circular RNA
 molecules, and circular genomes of bacteria, chloroplast, and
 mitochondria. One can also cluster climate data along any given
 longitude or latitude. Periodic data clustering can be formulated as
 circular clustering. The algorithms offer a general high-performance
 solution to circular, periodic, or framed data clustering. 
VignetteBuilder: knitr
License: LGPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
LinkingTo: Rcpp
Imports: Ckmeans.1d.dp, graphics, plotrix, Rcpp, stats
Suggests: ape, bazar, ggplot2, knitr, reshape2, rmarkdown, testthat
NeedsCompilation: yes
Packaged: 2020-12-13 07:10:45 UTC; joesong
Repository: CRAN
Date/Publication: 2020-12-15 22:30:21 UTC
