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ggm  

Graphical Markov Models with Mixed Graphs
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("ggm", "2.5.1")



Attach the package and use:
library("ggm")
Maintained by
Giovanni M. Marchetti
[Scholar Profile | Author Map]
First Published: 2003-09-12
Latest Update: 2024-01-25
Description:
Provides functions for defining mixed graphs containing three types of edges, directed, undirected and bi-directed, with possibly multiple edges. These graphs are useful because they capture fundamental independence structures in multivariate distributions and in the induced distributions after marginalization and conditioning. The package is especially concerned with Gaussian graphical models for (i) ML estimation for directed acyclic graphs, undirected and bi-directed graphs and ancestral graph models (ii) testing several conditional independencies (iii) checking global identification of DAG Gaussian models with one latent variable (iv) testing Markov equivalences and generating Markov equivalent graphs of specific types.
How to cite:
Giovanni M. Marchetti (2003). ggm: Graphical Markov Models with Mixed Graphs. R package version 2.5.1, https://cran.r-project.org/web/packages/ggm. Accessed 06 May. 2025.
Previous versions and publish date:
0.5 (2003-09-12 22:24), 0.8-1 (2003-11-15 22:29), 0.8 (2003-11-13 19:34), 1.0.2 (2006-02-09 15:52), 1.0.3 (2010-01-06 13:11), 1.0.4 (2010-02-15 09:23), 1.0 (2005-05-31 12:13), 1.99-1 (2011-12-11 11:41), 1.99-2 (2012-01-12 10:24), 1.99-3 (2012-06-14 17:04), 1.99-5 (2012-06-19 14:50), 1.99 (2011-11-23 14:11), 1.995-0 (2012-08-24 10:35), 1.995-2 (2012-09-14 14:06), 1.995-3 (2012-10-05 14:50), 1.995-5 (2014-01-15 19:40), 2.0 (2014-03-21 10:18), 2.1 (2014-05-19 11:43), 2.2 (2014-12-04 13:53), 2.3 (2015-01-21 12:47), 2.5 (2020-02-16 15:00)
Other packages that cited ggm R package
View ggm citation profile
Other R packages that ggm depends, imports, suggests or enhances
Complete documentation for ggm
Functions, R codes and Examples using the ggm R package
Some associated functions: AG . DAG . DG . In . InducedGraphs . MAG . MRG . MSG . MarkEqMag . MarkEqRcg . Max . RG . RepMarBG . RepMarDAG . RepMarUG . SG . SimpleGraphOperations . UG . UtilityFunctions . adjMatrix . allEdges . anger . basiSet . bfsearch . binve . blkdiag . blodiag . checkIdent . cmpGraph . conComp . correlations . cycleMatrix . dSep . derived . diagv . drawGraph . edgematrix . essentialGraph . findPath . fitAncestralGraph . fitConGraph . fitCovGraph . fitDag . fitDagLatent . fitmlogit . fundCycles . ggm . glucose . grMAT . icf . isADMG . isAG . isAcyclic . isGident . makeMG . marg.param . marks . mat.mlogit . msep . null . parcor . pcor . pcor.test . plotGraph . powerset . rcorr . rnormDag . rsphere . shipley.test . stress . surdata . swp . topSort . transClos . triDec . unmakeMG . 
Some associated R codes: all_functions.R .  Full ggm package functions and examples
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