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.

Version: 1.0
Depends: R (≥ 3.1.0), boot, cluster, depthTools, splines, splines2, stats
Imports: methods
Published: 2022-07-21
Author: Javier Albert Smet and Aurora Torrente. Alice Parodi, Mirco Patriarca, Laura Sangalli, Piercesare Secchi, Simone Vantini and Valeria Vitelli, as contributors.
Maintainer: Aurora Torrente <etorrent at est-econ.uc3m.es>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: briKmeans results

Documentation:

Reference manual: briKmeans.pdf

Downloads:

Package source: briKmeans_1.0.tar.gz
Windows binaries: r-devel: briKmeans_1.0.zip, r-release: briKmeans_1.0.zip, r-oldrel: briKmeans_1.0.zip
macOS binaries: r-release (arm64): briKmeans_1.0.tgz, r-oldrel (arm64): briKmeans_1.0.tgz, r-release (x86_64): briKmeans_1.0.tgz
Old sources: briKmeans archive

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