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HDclust: Clustering High Dimensional Data with Hidden Markov Model onVariable Blocks

Clustering of high dimensional data with Hidden Markov Model on Variable Blocks (HMM-VB) fitted via Baum-Welch algorithm. Clustering is performed by the Modal Baum-Welch algorithm (MBW), which finds modes of the density function. Lin Lin and Jia Li (2017) <https://jmlr.org/papers/v18/16-342.html>.

Version:1.0.4
Depends:methods
Imports:Rcpp (≥ 0.12.16),RcppProgress (≥ 0.1),Rtsne (≥ 0.11.0)
LinkingTo:Rcpp,RcppProgress
Suggests:knitr,rmarkdown
Published:2024-09-20
DOI:10.32614/CRAN.package.HDclust
Author:Yevhen Tupikov [aut], Lin Lin [aut], Lixiang Zhang [aut], Jia Li [aut, cre]
Maintainer:Jia Li <jiali at psu.edu>
License:GPL-2 |GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:yes
Materials:NEWS
CRAN checks:HDclust results

Documentation:

Reference manual:HDclust.html ,HDclust.pdf
Vignettes:A quick tour of HDclust (source,R code)

Downloads:

Package source: HDclust_1.0.4.tar.gz
Windows binaries: r-devel:HDclust_1.0.4.zip, r-release:HDclust_1.0.4.zip, r-oldrel:HDclust_1.0.4.zip
macOS binaries: r-release (arm64):HDclust_1.0.4.tgz, r-oldrel (arm64):HDclust_1.0.4.tgz, r-release (x86_64):HDclust_1.0.4.tgz, r-oldrel (x86_64):HDclust_1.0.4.tgz
Old sources: HDclust archive

Reverse dependencies:

Reverse suggests:OTclust

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=HDclustto link to this page.


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