Package: pmclust
Version: 0.1-8
Date: 2016-09-21
Title: Parallel Model-Based Clustering using
        Expectation-Gathering-Maximization Algorithm for Finite Mixture
        Gaussian Model
Authors@R: c(person("Wei-Chen", "Chen", role = c("aut", "cre"), email =
        "wccsnow@gmail.com"), person("George", "Ostrouchov", role = "aut"))
Depends: R (>= 3.0.0), pbdMPI (>= 0.3-1), pbdBASE (>= 0.4-3), pbdDMAT
        (>= 0.4-0)
Imports: methods, MASS
Enhances: MixSim
LazyLoad: yes
LazyData: yes
Description: Aims to utilize model-based clustering (unsupervised)
        for high dimensional and ultra large data, especially in a distributed
        manner. The code employs pbdMPI to perform a
        expectation-gathering-maximization 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 programming model. The code can be executed
        through pbdMPI and independent to most MPI applications.
        See the High Performance
        Statistical Computing website for more information, documents
        and examples.
License: GPL (>= 2)
URL: http://r-pbd.org/
BugReports: http://group.r-pbd.org/
MailingList: Please send questions and comments regarding pbdR to
        RBigData@gmail.com
NeedsCompilation: yes
Packaged: 2016-09-22 00:25:36 UTC; snoweye
Author: Wei-Chen Chen [aut, cre],
  George Ostrouchov [aut]
Maintainer: Wei-Chen Chen <wccsnow@gmail.com>
Repository: CRAN
Date/Publication: 2016-09-22 09:22:55
