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Package: pmclust
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Version: 0.1-7
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Date: 2016-06-07
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- Title: Parallel Model-Based Clustering
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+ Title: Parallel Model-Based Clustering using
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+ Expectation-Gathering-Maximization Algorithm for Finite Mixture
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+ Gaussian Model
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Authors@R: c(person("Wei-Chen", "Chen", role = c("aut", "cre"), email =
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"
[email protected] "), person("George", "Ostrouchov", role = "aut"))
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Depends: R (>= 3.0.0), pbdMPI (>= 0.3-1), pbdBASE (>= 0.4-3), pbdDMAT
@@ -10,24 +12,25 @@ Imports: methods, MASS
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Enhances: MixSim
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LazyLoad: yes
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LazyData: yes
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- Description: The pmclust aims to utilize model-based clustering (unsupervised)
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+ Description: Aims to utilize model-based clustering (unsupervised)
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for high dimensional and ultra large data, especially in a distributed
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- manner. The package employs Rmpi to perform a
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- expectation-gathering-maximization (EGM) algorithm
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+ manner. The code employs pbdMPI to perform a
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+ expectation-gathering-maximization algorithm
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for finite mixture Gaussian
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- models. The unstructured dispersion matrices are assumed in the Gaussian
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- models. The implementation is default in the single program multiple
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- data (SPMD) programming model. The code can be executed through Rmpi and
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- independent to most MPI applications. See the High Performance
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- Statistical Computing (HPSC) website for more information, documents
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+ models. The unstructured dispersion matrices are assumed in the
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+ Gaussian models. The implementation is default in the single program
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+ multiple data programming model. The code can be executed
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+ through pbdMPI and independent to most MPI applications.
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+ See the High Performance
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+ Statistical Computing website for more information, documents
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and examples.
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License: GPL (>= 2)
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URL: http://r-pbd.org/
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BugReports: http://group.r-pbd.org/
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MailingList: Please send questions and comments regarding pbdR to
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NeedsCompilation: yes
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- Packaged: 2016-01-24 16:48:25 UTC; snoweye
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+ Packaged: 2016-01-24 20:10:34 UTC; snoweye
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Author: Wei-Chen Chen [aut, cre],
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George Ostrouchov [aut]
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Maintainer: Wei-Chen Chen <
[email protected] >
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