Package: WCluster 1.3.0

WCluster: Clustering and PCA with Weights, and Data Nuggets Clustering

K-means clustering, hierarchical clustering, and PCA with observational weights and/or variable weights. It also includes the corresponding functions for data nuggets which serve as representative samples of large datasets. Cherasia et al., (2022) <doi:10.1007/978-3-031-22687-8_20>. Amaratunga et al., (2009) <doi:10.1002/9780470317129>.

Authors:Rituparna Dey [aut, cre], Yajie Duan [aut], Javier Cabrera [aut], Ge Cheng [aut]

WCluster_1.3.0.tar.gz
WCluster_1.3.0.zip(r-4.7-any)WCluster_1.3.0.zip(r-4.6-any)WCluster_1.3.0.zip(r-4.5-any)
WCluster_1.3.0.tgz(r-4.6-any)WCluster_1.3.0.tgz(r-4.5-any)
WCluster_1.3.0.tar.gz(r-4.7-any)WCluster_1.3.0.tar.gz(r-4.6-any)
WCluster_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
WCluster/json (API)

# Install 'WCluster' in R:
install.packages('WCluster', repos = c('https://ritde-art.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.38 score 24 scripts 248 downloads 12 exports 34 dependencies

Last updated from:483f740cb9. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK181
source / vignettesOK374
linux-releaseOK140
macos-releaseOK218
macos-oldrelOK194
windows-develOK105
windows-releaseOK122
windows-oldrelOK110
wasm-releaseOK109

Exports:cluster.predictdistwDN.WhclustDN.WkmeansDN.WpcaDNcluster.predictWhclustWkmeanswmeanWpcawsswwcss

Dependencies:cliclustercodetoolscpp11datanuggetdoParalleldoSNOWfarverforeachggplot2gluegtableisobanditeratorslabelinglatticelifecycleMatrixmgcvnlmeR6RColorBrewerRcppRcppArmadilloRcppParallelRfastrlangS7scalessnowvctrsviridisLitewithrzigg