Package: ggm 2.5.1

ggm: Graphical Markov Models with Mixed Graphs

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.

Authors:Giovanni M. Marchetti [aut, cre], Mathias Drton [aut], Kayvan Sadeghi [aut]

ggm_2.5.1.tar.gz
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ggm_2.5.1.tgz(r-4.4-any)ggm_2.5.1.tgz(r-4.3-any)
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ggm.pdf |ggm.html✨
ggm/json (API)
NEWS

# Install 'ggm' in R:
install.packages('ggm', repos = c('https://stathin.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/stathin/ggm/issues

Datasets:

On CRAN:

79 exports 4.75 score 14 dependencies 27 dependents 19 mentions 306 scripts 4.4k downloads

Last updated 8 months agofrom:a672d1af33. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 22 2024
R-4.5-winNOTEAug 22 2024
R-4.5-linuxNOTEAug 22 2024
R-4.4-winOKAug 22 2024
R-4.4-macOKAug 22 2024
R-4.3-winOKAug 22 2024
R-4.3-macOKAug 22 2024

Exports:adjMatrixAGallEdgesbasiSetbdbfsearchbinveblkdiagblodiagchcheckIdentcmpGraphconCompcorrelationscycleMatrixDAGDGdiagvdrawGraphdSepedgematrixessentialGraphfindPathfitAncestralGraphfitConGraphfitCovGraphfitDagfitDagLatentfitmlogitfundCyclesgrMATicficfmagIninducedChainGraphinducedConGraphinducedCovGraphinducedDAGinducedRegGraphisAcyclicisADMGisAGisGidentMAGmakeMGmarg.paramMarkEqMagMarkEqRcgmat.mlogitMaxMRGmsepMSGnullpaparcorpcorpcor.testplotGraphpowersetrcorrremRepMarBGRepMarDAGRepMarUGRGrnormDagRRrsphereSGshipley.testSPlswptopOrdertopSorttransClostriDecUGunmakeMG

Dependencies:BiocGenericsBiocManagerclicpp11gluegraphigraphlatticelifecyclemagrittrMatrixpkgconfigrlangvctrs

Readme and manuals

Help Manual

Help pageTopics
Adjacency matrix of a graphadjMatrix
Ancestral graphAG
All edges of a graphallEdges
Anger dataanger
Basis set of a DAGbasiSet
Breadth first searchbfsearch
Inverts a marginal log-linear parametrizationbinve
Block diagonal matrixblkdiag
Block diagonal matrixblodiag
Identifiability of a model with one latent variablecheckIdent
The complementary graphcmpGraph
Connectivity componentsconComp
Marginal and partial correlationscorrelations
Fundamental cyclescycleMatrix
Directed acyclic graphs (DAGs)DAG
Data on blood pressure body mass and agederived
Directed graphsDG
Matrix product with a diagonal matrixdiagv
Drawing a graph with a simple point and click interface.drawGraph
d-separationdSep
Edge matrix of a graphedgematrix
Essential graphessentialGraph
Finding pathsfindPath
Fitting of Gaussian Ancestral Graph ModelsfitAncestralGraph
Fitting a Gaussian concentration graph modelfitConGraph
Fitting of Gaussian covariance graph modelsfitCovGraph
Fitting of Gaussian DAG modelsfitDag
Fitting Gaussian DAG models with one latent variablefitDagLatent
Multivariate logistic modelsfitmlogit
Fundamental cyclesfundCycles
The package 'ggm': summary informationggm
Glucose controlglucose
Graph to adjacency matrixgrMAT
Indicator matrixIn
Graphs induced by marginalization or conditioninginducedChainGraph inducedConGraph inducedCovGraph inducedDAG InducedGraphs inducedRegGraph
Graph queriesisAcyclic
Acyclic directed mixed graphsisADMG
Ancestral graphisAG
G-identifiability of an UGisGident
Maximal ancestral graphMAG
Mixed GraphsmakeMG
Link function of marginal log-linear parameterizationmarg.param
Markov equivalence of maximal ancestral graphsMarkEqMag
Markov equivalence for regression chain graphs.MarkEqRcg
Mathematics marksmarks
Multivariate logistic parametrizationmat.mlogit
Maximisation for graphsMax
Maximal ribbonless graphMRG
The m-separation criterionmsep
Maximal summary graphMSG
Null space of a matrixnull
Partial correlationsparcor
Partial correlationpcor
Test for zero partial associationpcor.test
Plot of a mixed graphplotGraph
Power setpowerset
Random correlation matrixrcorr
Representational Markov equivalence to bidirected graphs.RepMarBG
Representational Markov equivalence to directed acyclic graphs.RepMarDAG
Representational Markov equivalence to undirected graphs.RepMarUG
Ribbonless graphRG
Random sample from a decomposable Gaussian modelrnormDag
Random vectors on a spherersphere
summary graphSG
Test of all independencies implied by a given DAGshipley.test
Simple graph operationsbd ch pa
Stressstress
A simulated data setsurdata
Sweep operatorswp
Topological sorttopOrder topSort
Transitive closure of a graphtransClos
Triangular decomposition of a covariance matrixtriDec
Defining an undirected graph (UG)UG
Loopless mixed graphs componentsunmakeMG
Utility functionslikGau rem RR SPl