The pmclust aims to utilize model-based clustering (unsupervised) for high dimensional and ultra large data, especially in a distributed manner. The package employs Rmpi to perform a expectation-gathering-maximization (EGM) algorithm for finite mixture Gaussian models. The unstructured dispersion matrices are assumed in the Gaussian models. The implementation is default in the single program multiple data (SPMD) programming model. The code can be executed through Rmpi and independent to most MPI applications. See the High Performance Statistical Computing (HPSC) website for more information, documents and examples.
| Version: | 0.1-4 |
| Depends: | R (≥ 2.14.0), methods, MASS, MixSim, rlecuyer, pbdMPI (≥ 0.1-6), pbdSLAP (≥ 0.1-5), pbdBASE (≥ 0.2-1), pbdDMAT (≥ 0.2-1) |
| Published: | 2013-03-25 |
| Author: | Wei-Chen Chen [aut, cre], George Ostrouchov [aut] |
| Maintainer: | Wei-Chen Chen <wccsnow at gmail.com> |
| BugReports: | http://group.r-pbd.org/ |
| License: | GPL (≥ 2) |
| URL: | http://r-pbd.org/ |
| NeedsCompilation: | yes |
| Citation: | pmclust citation info |
| In views: | Cluster, HighPerformanceComputing |
| CRAN checks: | pmclust results |
| Package source: | pmclust_0.1-4.tar.gz |
| MacOS X binary: | pmclust_0.1-4.tgz |
| Windows binary: | not available, see ReadMe. |
| Reference manual: | pmclust.pdf |
| Vignettes: |
pmclust-guide |
| News/ChangeLog: | ChangeLog |
| Old sources: | pmclust archive |