pcalg: Methods for Graphical Models and Causal Inference
Version 2.4-6

Functions for causal structure learning and causal inference using graphical models. The main algorithms for causal structure learning are PC (for observational data without hidden variables), FCI and RFCI (for observational data with hidden variables), and GIES (for a mix of data from observational studies (i.e. observational data) and data from experiments involving interventions (i.e. interventional data) without hidden variables). For causal inference the IDA algorithm, the Generalized Backdoor Criterion (GBC) and the Generalized Adjustment Criterion (GAC) are implemented.

AuthorMarkus Kalisch [aut, cre], Alain Hauser [aut], Martin Maechler [aut], Diego Colombo [ctb], Doris Entner [ctb], Patrik Hoyer [ctb], Antti Hyttinen [ctb], Jonas Peters [ctb], Nicoletta Andri [ctb], Emilija Perkovic [ctb], Preetam Nandy [ctb], Philipp Ruetimann [ctb], Daniel Stekhoven [ctb], Manuel Schuerch [ctb]
Date of publication2017-04-26 12:23:58
MaintainerMarkus Kalisch <kalisch@stat.math.ethz.ch>
LicenseGPL (>= 2)
Version2.4-6
URL http://pcalg.r-forge.r-project.org/
Package repositoryView on R-Forge
InstallationInstall the latest version of this package by entering the following in R:
install.packages("pcalg", repos="http://R-Forge.R-project.org")

Popular man pages

dag2cpdag: Convert a DAG to a CPDAG
fci: Estimate a PAG by the FCI Algorithm
fciPlus: Estimate a PAG by the FCI+ Algorithm
iplotPC: Plotting a pcAlgo object using the package igraph
pdag2dag: Extend a Partially Directed Acyclic Graph (PDAG) to a DAG
randomDAG: Generate a Directed Acyclic Graph (DAG) randomly
rmvDAG: Generate Multivariate Data according to a DAG
See all...

All man pages Function index File listing

Man pages

amatType: Types and Display of Adjacency Matrices in Package 'pcalg'
backdoor: Find Set Satisfying the Generalized Backdoor Criterion (GBC)
beta.special: Compute set of intervention effects
beta.special.pcObj: Compute set of intervention effects in a fast way
binCItest: G square Test for (Conditional) Independence of Binary...
checkTriple: Check Consistency of Conditional Independence for a Triple of...
compareGraphs: Compare two graphs in terms of TPR, FPR and TDR
condIndFisherZ: Test Conditional Independence of Gaussians via Fisher's Z
corGraph: Computing the correlation graph
dag2cpdag: Convert a DAG to a CPDAG
dag2essgraph: Convert a DAG to an Essential Graph
dag2pag: Convert a DAG with latent variables into a PAG
disCItest: G square Test for (Conditional) Independence of Discrete...
dreach: Compute D-SEP(x,y,G)
dsep: Test for d-separation in a DAG
dsepTest: Test for d-separation in a DAG
EssGraph-class: Class '"EssGraph"'
fci: Estimate a PAG by the FCI Algorithm
fciAlgo-class: Class "fciAlgo" of FCI Algorithm Results
fciPlus: Estimate a PAG by the FCI+ Algorithm
find.unsh.triple: Find all Unshielded Triples in an Undirected Graph
gac: Test If Set Satisfies Generalized Adjustment Criterion (GAC)
gAlgo-class: Class '"gAlgo"'
GaussL0penIntScore-class: Class '"GaussL0penIntScore"'
GaussL0penObsScore-class: Class '"GaussL0penObsScore"'
GaussParDAG-class: Class '"GaussParDAG"' of Gaussian Causal Models
gds: Greedy DAG Search to Estimate Markov Equivalence Class of DAG
ges: Estimate the Markov equivalence class of a DAG using GES
getGraph: Get the "graph" Part or Aspect of R Object
getNextSet: Iteration through a list of all combinations of choose(n,k)
gies: Estimate Interventional Markov Equivalence Class of a DAG by...
gmB: Graphical Model 5-Dim Binary Example Data
gmD: Graphical Model Discrete 5-Dim Example Data
gmG: Graphical Model 8-Dimensional Gaussian Example Data
gmI: Graphical Model 7-dim IDA Data Examples
gmInt: Graphical Model 8-Dimensional Interventional Gaussian Example...
gmL: Latent Variable 4-Dim Graphical Model Data Example
ida: Estimate Multiset of Possible Total Causal Effects
idaFast: Multiset of Possible Total Causal Effects for Several Target...
iplotPC: Plotting a pcAlgo object using the package igraph
jointIda: Estimate Multiset of Possible Total Joint Effects
legal.path: Check if a 3-node-path is Legal
LINGAM: Linear non-Gaussian Acyclic Models (LiNGAM)
mat2targets: Conversion between an intervention matrix and a list of...
mcor: Compute (Large) Correlation Matrix
pag2mag: Transform a PAG into a MAG in the Corresponding Markov...
ParDAG-class: Class '"ParDAG"' of Parametric Causal Models
pc: Estimate the Equivalence Class of a DAG using the PC...
pcalg-internal: Internal Pcalg Functions
pcAlgo: PC-Algorithm [OLD]: Estimate Skeleton or Equivalence Class of...
pcAlgo-class: Class "pcAlgo" of PC Algorithm Results, incl. Skeleton
pc.cons.intern: Utility for conservative and majority rule in PC and FCI
pcorOrder: Compute Partial Correlations
pcSelect: PC-Select: Estimate subgraph around a response variable
pcSelect.presel: Estimate Subgraph around a Response Variable using...
pdag2allDags: Enumerate All DAGs in a Markov Equivalence Class
pdag2dag: Extend a Partially Directed Acyclic Graph (PDAG) to a DAG
pdsep: Estimate Final Skeleton in the FCI algorithm
plotAG: Plot partial ancestral graphs (PAG)
plotSG: Plot the subgraph around a Specific Node in a Graph Object
possibleDe: Find possible descendants on definite status paths.
qreach: Compute Possible-D-SEP(x,G) of a node x in a PDAG G
randDAG: Random DAG Generation
randomDAG: Generate a Directed Acyclic Graph (DAG) randomly
rfci: Estimate an RFCI-PAG using the RFCI Algorithm
r.gauss.pardag: Generate a Gaussian Causal Model Randomly
rmvDAG: Generate Multivariate Data according to a DAG
rmvnorm.ivent: Simulate from a Gaussian Causal Model
Score-class: Virtual Class "Score"
shd: Compute Structural Hamming Distance (SHD)
showAmat: Show Adjacency Matrix of pcAlgo object
showEdgeList: Show Edge List of pcAlgo object
simy: Estimate Interventional Markov Equivalence Class of a DAG
skeleton: Estimate (Initial) Skeleton of a DAG using the PC / PC-Stable...
trueCov: Covariance matrix of a DAG.
udag2apag: Last step of RFCI algorithm: Transform partially oriented...
udag2pag: Last steps of FCI algorithm: Transform Final Skeleton into...
udag2pdag: Last PC Algorithm Step: Extend Object with Skeleton to...
unifDAG: Uniform Sampling of Directed Acyclic Graphs (DAG)
visibleEdge: Check visible edge.
wgtMatrix: Weight Matrix of a Graph, e.g., a simulated DAG

Functions

Files

ChangeLog
DESCRIPTION
NAMESPACE
R
R/Aaux.R
R/AllClasses.R
R/deprecated.R
R/gacFuns.R
R/genRandDAG.R
R/gies.R
R/jointIda.R
R/lingamFuns.R
R/pcalg.R
R/sysdata.rda
R/zzz.R
TODO
build
build/vignette.rds
cleanup
data
data/datalist
data/gmB.rda
data/gmD.rda
data/gmG.rda
data/gmI.rda
data/gmInt.rda
data/gmL.rda
inst
inst/CITATION
inst/NEWS.Rd
inst/doc
inst/doc/mkVignettes.R
inst/doc/pcalgDoc.R
inst/doc/pcalgDoc.Rnw
inst/doc/pcalgDoc.pdf
inst/external
inst/external/N_6_1000.rds
inst/external/gac-pags.rds
inst/external/test_conservative_pc_data1.rda
inst/external/test_conservative_pc_data2.rda
inst/include
inst/include/pcalg
inst/include/pcalg/armaLapack.hpp
inst/include/pcalg/constraint.hpp
inst/include/pcalg/gies_debug.hpp
inst/include/pcalg/greedy.hpp
inst/include/pcalg/score.hpp
inst/xtraR
inst/xtraR/graph2ftmatrix.R
man
man/EssGraph-class.Rd
man/GaussL0penIntScore-class.Rd
man/GaussL0penObsScore-class.Rd
man/GaussParDAG-class.Rd
man/LINGAM.Rd
man/ParDAG-class.Rd
man/Score-class.Rd
man/amatType.Rd
man/backdoor.Rd
man/beta.special.Rd
man/beta.special.pcObj.Rd
man/binCItest.Rd
man/checkTriple.Rd
man/compareGraphs.Rd
man/condIndFisherZ.Rd
man/corGraph.Rd
man/dag2cpdag.Rd
man/dag2essgraph.Rd
man/dag2pag.Rd
man/disCItest.Rd
man/dreach.Rd
man/dsep.Rd
man/dsepTest.Rd
man/fci.Rd
man/fciAlgo-class.Rd
man/fciPlus.Rd
man/find.unsh.triple.Rd
man/gAlgo-class.Rd
man/gac.Rd
man/gds.Rd
man/ges.Rd
man/getGraph.Rd
man/getNextSet.Rd
man/gies.Rd
man/gmB.Rd
man/gmD.Rd
man/gmG.Rd
man/gmI.Rd
man/gmInt.Rd
man/gmL.Rd
man/ida.Rd
man/idaFast.Rd
man/iplotPC.Rd
man/jointIda.Rd
man/legal.path.Rd
man/mat2targets.Rd
man/mcor.Rd
man/pag2mag.Rd
man/pc.Rd
man/pc.cons.intern.Rd
man/pcAlgo-class.Rd
man/pcAlgo.Rd
man/pcSelect.Rd
man/pcSelect.presel.Rd
man/pcalg-internal.Rd
man/pcorOrder.Rd
man/pdag2allDags.Rd
man/pdag2dag.Rd
man/pdsep.Rd
man/plotAG.Rd
man/plotSG.Rd
man/possibleDe.Rd
man/qreach.Rd
man/r.gauss.pardag.Rd
man/randDAG.Rd
man/randomDAG.Rd
man/rfci.Rd
man/rmvDAG.Rd
man/rmvnorm.ivent.Rd
man/shd.Rd
man/showAmat.Rd
man/showEdgeList.Rd
man/simy.Rd
man/skeleton.Rd
man/trueCov.Rd
man/udag2apag.Rd
man/udag2pag.Rd
man/udag2pdag.Rd
man/unifDAG.Rd
man/visibleEdge.Rd
man/wgtMatrix.Rd
src
src/Makevars
src/Makevars.win
src/constraint.cpp
src/gies.cpp
src/greedy.cpp
src/init.c
src/score.cpp
tests
tests/discr100k.rda
tests/test_LINGAM.R
tests/test_amat2dag.R
tests/test_arges.R
tests/test_backdoor.R
tests/test_backdoor.Rout.save
tests/test_bicscore.R
tests/test_bicscore.rda
tests/test_causalEffect.R
tests/test_compareGraphs.R
tests/test_dag2cpdag.R
tests/test_dag2essgraph.R
tests/test_displayAmat.R
tests/test_dsep.R
tests/test_fci.R
tests/test_fciPlus.R
tests/test_gSquareBin.R
tests/test_gSquareDis.R
tests/test_gac.R
tests/test_getNextSet.R
tests/test_gies.R
tests/test_ida.R
tests/test_idaFast.R
tests/test_jointIda.R
tests/test_mat2targets.R
tests/test_pc.R
tests/test_pcSelect.R
tests/test_pcorOrder.R
tests/test_pdag2allDags.R
tests/test_pdag2dag.R
tests/test_randDAG.R
tests/test_randDAG.Rout.save
tests/test_randomDAG.R
tests/test_rfci.R
tests/test_rmvDAG.R
tests/test_shd.R
tests/test_skeleton.R
tests/test_udag2pag.R
tests/test_udag2pdag.R
tests/test_unifDAG.R
tests/test_wgtMatrix.R
vignettes
vignettes/Figure1FAT.pdf
vignettes/Figure2FAT.pdf
vignettes/Mybib.bib
vignettes/jsslogo.jpg
vignettes/pcalgDoc.Rnw
pcalg documentation built on May 21, 2017, 1:07 a.m.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs in the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.