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: |
0.1-6 |
| Depends: |
R (≥ 3.0.0), methods, rlecuyer, pbdMPI (≥ 0.2-2), MASS |
| Enhances: |
MixSim, pbdSLAP (≥ 0.1-7), pbdBASE (≥ 0.3-0), pbdDMAT (≥
0.2-4) |
| Published: |
2014-02-03 |
| 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 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
http://r-pbd.org/ |
| NeedsCompilation: |
yes |
| Citation: |
pmclust citation info |
| Materials: |
README ChangeLog |
| In views: |
Cluster, HighPerformanceComputing |
| CRAN checks: |
pmclust results |