Implementation of the BRIk and FABRIk 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 (2020) <doi:10.1007/s00357-020-09372-3>.
| Version: | 0.1 |
| Depends: | R (≥ 3.1.0), boot, cluster, depthTools |
| Published: | 2021-02-15 |
| Author: | Javier Albert Smet and Aurora Torrente. |
| Maintainer: | Aurora Torrente <etorrent at est-econ.uc3m.es> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | briKmeans results |
| Reference manual: | briKmeans.pdf |
| Package source: | briKmeans_0.1.tar.gz |
| Windows binaries: | r-devel: briKmeans_0.1.zip, r-release: briKmeans_0.1.zip, r-oldrel: briKmeans_0.1.zip |
| macOS binaries: | r-release: briKmeans_0.1.tgz, r-oldrel: briKmeans_0.1.tgz |
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