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.
| Version: | 4.3.5 | 
| Imports: | Rcpp, Rdpack (≥ 0.6-1) | 
| LinkingTo: | Rcpp | 
| Suggests: | testthat, knitr, rmarkdown, RColorBrewer | 
| Published: | 2023-08-19 | 
| DOI: | 10.32614/CRAN.package.Ckmeans.1d.dp | 
| Author: | Joe Song | 
| Maintainer: | Joe Song <joemsong at cs.nmsu.edu> | 
| License: | LGPL (≥ 3) | 
| NeedsCompilation: | yes | 
| Citation: | Ckmeans.1d.dp citation info | 
| Materials: | README, NEWS | 
| CRAN checks: | Ckmeans.1d.dp results | 
| Reference manual: | Ckmeans.1d.dp.html , Ckmeans.1d.dp.pdf | 
| Vignettes: | Tutorial: Optimal univariate clustering (source, R code) Note: Weight scaling in cluster analysis (source) Tutorial: Adaptive versus regular histograms (source, R code) | 
| Package source: | Ckmeans.1d.dp_4.3.5.tar.gz | 
| Windows binaries: | r-devel: Ckmeans.1d.dp_4.3.5.zip, r-release: Ckmeans.1d.dp_4.3.5.zip, r-oldrel: Ckmeans.1d.dp_4.3.5.zip | 
| macOS binaries: | r-release (arm64): Ckmeans.1d.dp_4.3.5.tgz, r-oldrel (arm64): Ckmeans.1d.dp_4.3.5.tgz, r-release (x86_64): Ckmeans.1d.dp_4.3.5.tgz, r-oldrel (x86_64): Ckmeans.1d.dp_4.3.5.tgz | 
| Old sources: | Ckmeans.1d.dp archive | 
| Reverse depends: | GenomicOZone | 
| Reverse imports: | autostats, CellBarcode, clusterHD, GridOnClusters, Harman, kcmeans, OptCirClust, SILFS, SPECK, STREAK, TidyConsultant, weitrix | 
| Reverse suggests: | bakR, CytoProfile, DiffXTables, FunChisq, mapsf, xgboost | 
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