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 |
DOI: |
10.32614/CRAN.package.briKmeans |
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:
Downloads:
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