Clustering algorithm for high dimensional data. Assuming that P feature measurements on N objects are arranged in an N×P matrix X, this package provides clustering based on the left Gram matrix XX^T. To simulate test data, type "help('simulate_HD_data')" and to learn how to use the clustering algorithm, type "help('RJclust')". To cite this package, type 'citation("RJcluster")'.
| Version: | 3.2.4 |
| Depends: | R (≥ 2.10) |
| Imports: | Rcpp (≥ 1.0.2), matrixStats, infotheo, rlang, stats, graphics, profvis, mclust, foreach, utils |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | testthat (≥ 2.1.0), knitr, rmarkdown |
| Published: | 2022-02-14 |
| DOI: | 10.32614/CRAN.package.RJcluster |
| Author: | Shahina Rahman [aut], Valen E. Johnson [aut], Suhasini Subba Rao [aut], Rachael Shudde [aut, cre, trl] |
| 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 [issues need fixing before 2025-04-14] |
| Reference manual: | RJcluster.pdf |
| Vignettes: |
RJclust_Vignette (source, R code) |
| Package source: | RJcluster_3.2.4.tar.gz |
| Windows binaries: | r-devel: RJcluster_3.2.4.zip, r-release: RJcluster_3.2.4.zip, r-oldrel: RJcluster_3.2.4.zip |
| macOS binaries: | r-devel (arm64): RJcluster_3.2.4.tgz, r-release (arm64): RJcluster_3.2.4.tgz, r-oldrel (arm64): RJcluster_3.2.4.tgz, r-devel (x86_64): RJcluster_3.2.4.tgz, r-release (x86_64): RJcluster_3.2.4.tgz, r-oldrel (x86_64): RJcluster_3.2.4.tgz |
| Old sources: | RJcluster archive |
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