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gmgm  

Gaussian Mixture Graphical Model Learning and Inference
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("gmgm", "1.1.2")



Attach the package and use:
library("gmgm")
Maintained by
Jérémy Roos
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-11-11
Latest Update: 2022-09-08
Description:
Gaussian mixture graphical models include Bayesian networks and dynamic Bayesian networks (their temporal extension) whose local probability distributions are described by Gaussian mixture models. They are powerful tools for graphically and quantitatively representing nonlinear dependencies between continuous variables. This package provides a complete framework to create, manipulate, learn the structure and the parameters, and perform inference in these models. Most of the algorithms are described in the PhD thesis of Roos (2018) .
How to cite:
Jérémy Roos (2020). gmgm: Gaussian Mixture Graphical Model Learning and Inference. R package version 1.1.2, https://cran.r-project.org/web/packages/gmgm. Accessed 06 Aug. 2026.
Previous versions and publish date:
(2026-07-09 07:44), 1.0.0 (2020-11-11 16:20), 1.0.1 (2020-11-14 14:40), 1.0.2 (2021-04-17 06:30), 1.1.0 (2021-09-02 19:00), 1.1.1 (2022-05-27 20:40), 1.1.2 (2022-09-08 22:32)
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Complete documentation for gmgm
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