Performs clustering of quantitative variables, assuming that clusters lie in low-dimensional subspaces. Segmentation of variables, number of clusters and their dimensions are selected based on BIC. Candidate models are identified based on many runs of K-means algorithm with different random initializations of cluster centers.
| Version: | 0.9.4 |
| Depends: | R (≥ 3.2.1) |
| Imports: | RcppEigen, foreach, parallel, doParallel, doRNG, pesel |
| Suggests: | knitr, mclust, rmarkdown, testthat |
| Published: | 2019-06-26 |
| Author: | Piotr Sobczyk, Stanislaw Wilczynski, Julie Josse, Malgorzata Bogdan |
| Maintainer: | Piotr Sobczyk <pj.sobczyk at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | varclust results |
| Reference manual: | varclust.pdf |
| Vignettes: |
varclust tutorial |
| Package source: | varclust_0.9.4.tar.gz |
| Windows binaries: | r-devel: varclust_0.9.4.zip, r-release: varclust_0.9.4.zip, r-oldrel: varclust_0.9.4.zip |
| macOS binaries: | r-release: varclust_0.9.4.tgz, r-oldrel: varclust_0.9.4.tgz |
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