Clustering algorithm for high dimensional data. This algorithm is ideal for data where n << p.
Version: | 0.1.0 |
Depends: | R (≥ 2.10) |
Imports: | Rcpp (≥ 1.0.2), matrixStats, infotheo, rlang, stats, graphics, profvis, mclust, doParallel, foreach, parallel |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | testthat (≥ 2.1.0), knitr, rmarkdown |
Published: | 2020-09-23 |
Author: | Rachael Shudde [aut, cre], Shahina Rahman [aut], Valen Johnson [aut] |
Maintainer: | Rachael Shudde <rachael.shudde at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
Materials: | README |
CRAN checks: | RJcluster results |
Reference manual: | RJcluster.pdf |
Vignettes: |
RJclust_Vignette |
Package source: | RJcluster_0.1.0.tar.gz |
Windows binaries: | r-devel: RJcluster_0.1.0.zip, r-release: RJcluster_0.1.0.zip, r-oldrel: RJcluster_0.1.0.zip |
macOS binaries: | r-release: RJcluster_0.1.0.tgz, r-oldrel: RJcluster_0.1.0.tgz |
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