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)WCluster_1.3.0.zip(r-4.6)WCluster_1.3.0.zip(r-4.5)
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
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.

1.28 score 19 scripts 209 downloads 12 exports 12 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64OK150
source / vignettesOK162
linux-release-x86_64OK126
macos-release-arm64OK114
macos-oldrel-arm64OK97
windows-develOK85
windows-releaseOK92
windows-oldrelOK72
wasm-releaseOK92

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

Dependencies:clustercodetoolsdatanuggetdoSNOWforeachiteratorsRcppRcppArmadilloRcppParallelRfastsnowzigg