Learn R Programming
⚠️There's a newer version (2.5.2) of this package.Take me there.

ggm (version 0.5)

Graphical Gaussian Models

Description

Functions for defining directed acyclic graphs and undirected graphs, finding induced graphs and fitting Gaussian Markov models.

Copy Link

Version

Install

install.packages('ggm')

Monthly Downloads

6,060

Version

0.5

License

GPL version 2 or newer

Maintainer

Giovanni Marchetti

Last Published

July 25th, 2025

Functions in ggm (0.5)

bfs

Breadth first search
checkIdent

Identifiability of a model with one latent variable
Ancestors

Ancestor graphs
cycleMatrix

Fundamental cycles
edges

Edges of a graph
DAG

Defining directed acyclic graphs (DAGs)
cliques

Cliques of an undirected graph
topSort

Topological sort
In

Indicator matrix
conComp

Connectivity components
cmpGraph

The complementary graph
parcor

Partial correlations
is.acyclic

Graph queries
fitUg

Gaussian Markov models specified by an UG
shipley.test

Test of all independencies implied by a DAG
fitDagLatent

Gaussian DAG model with one latent variable
glucose

Glucose control
rnormDag

Random sample from a decomposable Gaussian model
is.Gident

G-identifiability of an UG
rsphere

Random vectors on a sphere
marks

Mathematics marks
rcorr

Random correlation matrix
clos

Graph operations
InducedGraphs

Graphs induced by marginalization or conditioning
basiSet

Basis set of a DAG
swp

Sweep operator
UG

Defining an undirected graph (UG)
fitDag

Gaussian Markov models specified by a DAG
pcor.test

Test for zero partial association
fundCycles

Fundamental cycles
Simple Graph Operations

Simple graph operations
findPath

Finding paths
dSep

d-separation
correlations

Marginal and partial correlations
pcor

Partial correlation
triDec

Triangular decomposition of a covariance matrix