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pmclust
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]
[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 26 Oct. 2026.
Previous versions and publish date:
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Other R packages that pmclust depends,
imports, suggests or enhances
Complete documentation for pmclust
Functions, R codes and Examples using
the pmclust R package
Some associated functions: 00_pmclust-package . 01-pmclust_pkmeans . 10_d.readme . 11_d.set.global . 12_d.param . 13_d.control . 20-assign.N.sample . 30-em.one.e . 30-em.one.m . 30-em.one . 30-em_initial . 30-em_like . 40-generate.MixSim . 40-generate.basic . 41-get.N.CLASS . 50-indep.logL . 50-mb.print . 50-update.class . 60-print . zz-internal .
Some associated R codes: Full pmclust package functions and examples
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