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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.
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2.5.1
2.5
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1.995-5
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0.5
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Install
install.packages('ggm')
Monthly Downloads
5,124
Version
0.5
License
GPL version 2 or newer
Maintainer
Giovanni Marchetti
Last Published
August 23rd, 2003
Functions in ggm (0.5)
Search functions
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