Package: r-cran-ckmeans.1d.dp
Version: 4.3.5+dfsg-1
Architecture: amd64
Maintainer: Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
Original-Maintainer: Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
Installed-Size: 396
Depends: r-api-4.0, r-cran-rcpp, r-cran-rdpack (>= 0.6-1), libc6 (>= 2.29), libgcc-s1 (>= 3.0), libstdc++6 (>= 14)
Recommends: r-cran-testthat, r-cran-knitr, r-cran-rmarkdown, r-cran-rcolorbrewer
Section: gnu-r
Priority: optional
Homepage: https://cran.r-project.org/package=Ckmeans.1d.dp
Description: Optimal, Fast, and Reproducible Univariate Clustering
 Fast, optimal, and reproducible weighted univariate clustering by
 dynamic programming. Four problems are solved, including univariate k-means
 (Wang & Song 2011) <doi:10.32614/RJ-2011-015> (Song & Zhong 2020)
 <doi:10.1093/bioinformatics/btaa613>, k-median, k-segments, and
 multi-channel weighted k-means. Dynamic programming is used to minimize
 the sum of (weighted) within-cluster distances using respective metrics.
 Its advantage over heuristic clustering in efficiency and accuracy is
 pronounced when there are many clusters. Multi-channel weighted k-means groups
 multiple univariate signals into k clusters. An auxiliary function generates
 histograms adaptive to patterns in data. This package provides a powerful
 set of tools for univariate data analysis with guaranteed optimality,
 efficiency, and reproducibility, useful for peak calling on temporal, spatial,
 and spectral data.
