DESCRIPTION

Package: pmclust
Version: 0.2-2
Date: 2023-09-03
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 (>= 0.4-2)
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 MPI' implementations such as 'OpenMPI'
        and 'MPICH'.
        See the High Performance Statistical Computing website
	<https://snoweye.github.io/hpsc/>
	for more information, documents and examples.
License: GPL (>= 2)
URL: https://pbdr.org/
BugReports: https://github.com/snoweye/pmclust/issues
MailingList: Please send questions and comments to wccsnow@gmail.com
NeedsCompilation: yes
Maintainer: Wei-Chen Chen <wccsnow@gmail.com>