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mcclust  

Process an MCMC Sample of Clusterings
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("mcclust", "1.0.1")



Attach the package and use:
library("mcclust")
Maintained by
Arno Fritsch
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-07-23
Latest Update: 2022-05-02
Description:
Implements methods for processing a sample of (hard) clusterings, e.g. the MCMC output of a Bayesian clustering model. Among them are methods that find a single best clustering to represent the sample, which are based on the posterior similarity matrix or a relabelling algorithm.
How to cite:
Arno Fritsch (2012). mcclust: Process an MCMC Sample of Clusterings. R package version 1.0.1, https://cran.r-project.org/web/packages/mcclust. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0 (2012-07-23 10:35)
Other packages that cited mcclust R package
View mcclust citation profile
Other R packages that mcclust depends, imports, suggests or enhances
Complete documentation for mcclust
Functions, R codes and Examples using the mcclust R package
Some associated functions: Ysim1.5 . Ysim2 . arandi . cls.draw1.5 . cls.draw2 . cltoSim . comp.psm . maxpear . mcclust-package . medv . minbinder . norm.label . relabel . vi.dist . 
Some associated R codes: Simtocl.R . arandi.R . binder.R . cltoSim.R . comp.psm.R . laugreen.R . maxpear.R . medv.R . minbinder.R . norm.label.R . pear.R . relabel.R . vi.dist.R .  Full mcclust package functions and examples
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