Package: briKmeans 1.0

briKmeans: Package for Brik, Fabrik and Fdebrik Algorithms to Initialise Kmeans

Implementation of the BRIk, FABRIk and FDEBRIk algorithms to initialise k-means. These methods are intended for the clustering of multivariate and functional data, respectively. They make use of the Modified Band Depth and bootstrap to identify appropriate initial seeds for k-means, which are proven to be better options than many techniques in the literature. Torrente and Romo (2021) <doi:10.1007/s00357-020-09372-3> It makes use of the functions kma and kma.similarity, from the archived package fdakma, by Alice Parodi et al.

Authors:Javier Albert Smet <[email protected]> and Aurora Torrente <[email protected]>. Alice Parodi, Mirco Patriarca, Laura Sangalli, Piercesare Secchi, Simone Vantini and Valeria Vitelli, as contributors.

briKmeans_1.0.tar.gz
briKmeans_1.0.zip(r-4.7)briKmeans_1.0.zip(r-4.6)briKmeans_1.0.zip(r-4.5)
briKmeans_1.0.tgz(r-4.6-any)briKmeans_1.0.tgz(r-4.5-any)
briKmeans_1.0.tar.gz(r-4.7-any)briKmeans_1.0.tar.gz(r-4.6-any)
briKmeans_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
briKmeans/json (API)

# Install 'briKmeans' in R:
install.packages('briKmeans', repos = c('https://aurora-torrente.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.

1.00 score 214 downloads 7 exports 6 dependencies

Last updated from:cff507e4da. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK181
source / vignettesOK152
linux-release-x86_64OK107
macos-release-arm64OK77
macos-oldrel-arm64OK80
windows-develOK78
windows-releaseOK79
windows-oldrelOK77
wasm-releaseOK94

Exports:brikelbowRulefabrikfdebrikkmakma.similarityplotKmeansClustering

Dependencies:bootclusterdepthToolsRcppRcppArmadillosplines2