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pmclust  

Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model
View on CRAN: Click here


Download and install pmclust package within the R console
Install from CRAN:
install.packages("pmclust")

Install from Github:
library("remotes")
install_github("cran/pmclust")

Install by package version:
library("remotes")
install_version("pmclust", "0.2-1")



Attach the package and use:
library("pmclust")
Maintained by
Wei-Chen Chen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-02-08
Latest Update: 2021-02-11
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 MPI' implementations such as 'OpenMPI' and 'MPICH'. See the High Performance Statistical Computing website for more information, documents and examples.
How to cite:
Wei-Chen Chen (2012). pmclust: Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model. R package version 0.2-1, https://cran.r-project.org/web/packages/pmclust. Accessed 25 Aug. 2026.
Previous versions and publish date:
(2026-07-09 06:42), 0.1-1 (2012-02-08 19:27), 0.1-2 (2012-03-10 07:34), 0.1-3 (2013-01-01 07:41), 0.1-4 (2013-03-25 15:43), 0.1-5 (2013-07-03 16:33), 0.1-6 (2014-02-03 07:12), 0.1-7 (2016-01-26 00:26), 0.1-8 (2016-09-22 09:22), 0.1-9 (2016-12-19 08:34), 0.2-0 (2018-02-02 05:41)
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Complete documentation for pmclust
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