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Various quantile-based clustering algorithms: algorithm CU (Common theta and Unscaled variables), algorithm CS (Common theta and Scaled variables through lambda_j), algorithm VU (Variable-wise theta_j and Unscaled variables) and algorithm VW (Variable-wise theta_j and Scaled variables through lambda_j). Hennig, C., Viroli, C., Anderlucci, L. (2019) "Quantile-based clustering." Electronic Journal of Statistics. 13 (2) 4849 - 4883 <doi:10.1214/19-EJS1640>.
| Version: | 1.0.1 |
| Imports: | stats |
| Published: | 2022-05-26 |
| DOI: | 10.32614/CRAN.package.QuClu |
| Author: | Christian Hennig, Cinzia Viroli and Laura Anderlucci |
| Maintainer: | Laura Anderlucci <laura.anderlucci at unibo.it> |
| License: | GPL-2 | GPL-3 |
| NeedsCompilation: | no |
| In views: | Cluster |
| CRAN checks: | QuClu results |
| Reference manual: | QuClu.pdf |
| Package source: | QuClu_1.0.1.tar.gz |
| Windows binaries: | r-devel: QuClu_1.0.1.zip, r-release: QuClu_1.0.1.zip, r-oldrel: QuClu_1.0.1.zip |
| macOS binaries: | r-release (arm64): QuClu_1.0.1.tgz, r-oldrel (arm64): QuClu_1.0.1.tgz, r-release (x86_64): QuClu_1.0.1.tgz, r-oldrel (x86_64): QuClu_1.0.1.tgz |
| Old sources: | QuClu archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.