Unsupervised clustering protocol for large scale structured data, based on a low dimensional representation of the data. Dimensionality reduction is performed using a parallelized implementation of the t-Stochastic Neighboring Embedding algorithm (Garriga J. and Bartumeus F. (2018), <arXiv:1812.09869>).
| Version: | 2.1.0 |
| Depends: | R (≥ 3.4.0) |
| Imports: | Rcpp (≥ 0.12.0), bigmemory (≥ 4.5.0), parallel (≥ 3.5.0), RColorBrewer, colorspace |
| LinkingTo: | Rcpp, RcppArmadillo, BH, bigmemory |
| Suggests: | snow (≥ 0.4-2), Rmpi (≥ 0.6-7), knitr, rmarkdown |
| Published: | 2019-03-01 |
| Author: | Joan Garriga [aut, cre], Frederic Bartumeus [aut] |
| Maintainer: | Joan Garriga <jgarriga at ceab.csic.es> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| SystemRequirements: | GNU make |
| Materials: | NEWS |
| CRAN checks: | bigMap results |
| Reference manual: | bigMap.pdf |
| Vignettes: |
The bigMap R-package: quick reference |
| Package source: | bigMap_2.1.0.tar.gz |
| Windows binaries: | r-devel: bigMap_2.1.0.zip, r-release: bigMap_2.1.0.zip, r-oldrel: bigMap_2.1.0.zip |
| OS X binaries: | r-release: bigMap_2.1.0.tgz, r-oldrel: bigMap_2.1.0.tgz |
| Old sources: | bigMap archive |
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