R: Methods for Graphical Models and Causal Inference

# Methods for Graphical Models and Causal Inference

## Documentation for package ‘pcalg’ version 2.7-12

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

A B C D E F G I J L M O P Q R S T U V W Z

## -- A --

addBgKnowledge | Add background knowledge to a CPDAG or PDAG
adjustment | Compute adjustment sets for covariate adjustment.
ages | Estimate an APDAG within the Markov equivalence class of a DAG using AGES
amat.cpdag | Types and Display of Adjacency Matrices in Package 'pcalg'
amat.pag | Types and Display of Adjacency Matrices in Package 'pcalg'
amatType | Types and Display of Adjacency Matrices in Package 'pcalg'

## -- B --

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 Variables

## -- C --

causalEffect | Estimate Multiset of Possible Joint Total Causal Effects
checkTriple | Check Consistency of Conditional Independence for a Triple of Nodes
coerce-method | Types and Display of Adjacency Matrices in Package 'pcalg'
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

## -- D --

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 Variables
dreach | Compute D-SEP(x,y,G)
dsep | Test for d-separation in a DAG
dsepAM | Test for d-separation in a MAG
dsepAMTest | Test for d-separation in a MAG
dsepTest | Test for d-separation in a DAG

## -- E --

EssGraph-class | Class '"EssGraph"'

## -- F --

fci | Estimate a PAG with the FCI Algorithm
fciAlgo-class | Class "fciAlgo" of FCI Algorithm Results
fciPlus | Estimate a PAG with the FCI+ Algorithm
find.unsh.triple | Find all Unshielded Triples in an Undirected Graph

## -- G --

gac | Test If Set Satisfies Generalized Adjustment Criterion (GAC)
gAlgo-class | Class '"gAlgo"'
gaussCItest | Test Conditional Independence of Gaussians via Fisher's Z
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
getGraph-method | Get the "graph" Part or Aspect of R Object
getGraph-methods | 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 GIES
global.mle-method | Class '"GaussL0penIntScore"'
global.mle-method | Class '"GaussL0penObsScore"'
global.score-method | Class '"GaussL0penIntScore"'
global.score-method | Class '"GaussL0penObsScore"'
gmB | Graphical Model 5-Dim Binary Example Data
gmD | Graphical Model Discrete 5-Dim Example Data
gmG | Graphical Model 8-Dimensional Gaussian Example Data
gmG8 | Graphical Model 8-Dimensional Gaussian Example Data
gmI | Graphical Model 7-dim IDA Data Examples
gmI7 | Graphical Model 7-dim IDA Data Examples
gmInt | Graphical Model 8-Dimensional Interventional Gaussian Example Data
gmL | Latent Variable 4-Dim Graphical Model Data Example
gSquareBin | G square Test for (Conditional) Independence of Binary Variables
gSquareDis | G square Test for (Conditional) Independence of Discrete Variables

## -- I --

ida | Estimate Multiset of Possible Joint Total Causal Effects
idaFast | Multiset of Possible Total Causal Effects for Several Target Var.s
iplotPC | Plotting a pcAlgo object using the package igraph
isValidGraph | Check for a DAG, CPDAG or a maximally oriented PDAG

## -- J --

jointIda | Estimate Multiset of Possible Total Joint Effects

## -- L --

legal.path | Check if a 3-node-path is Legal
LINGAM | Linear non-Gaussian Acyclic Models (LiNGAM)
lingam | Linear non-Gaussian Acyclic Models (LiNGAM)
local.mle-method | Class '"GaussL0penIntScore"'
local.mle-method | Class '"GaussL0penObsScore"'
local.score-method | Class '"GaussL0penIntScore"'
local.score-method | Class '"GaussL0penObsScore"'

## -- M --

mat2targets | Conversion between an intervention matrix and a list of intervention targets
mcor | Compute (Large) Correlation Matrix

## -- O --

opt.target | Get an optimal intervention target
optAdjSet | Compute the optimal adjustment set

## -- P --

pag2anc | Reads off identifiable ancestors and non-ancestors from a directed PAG
pag2conf | Reads off identifiable unconfounded node pairs from a directed PAG
pag2edge | Reads off identifiable parents and non-parents from a directed PAG
pag2magAM | Transform a PAG into a MAG in the Corresponding Markov Equivalence Class
ParDAG-class | Class '"ParDAG"' of Parametric Causal Models
pc | Estimate the Equivalence Class of a DAG using the PC Algorithm
pc.cons.intern | Utility for conservative and majority rule in PC and FCI
pcalg2dagitty | Transform the adjacency matrix from 'pcalg' into a 'dagitty' object
pcAlgo | PC-Algorithm [OLD]: Estimate Skeleton or Equivalence Class of a DAG
pcAlgo-class | Class "pcAlgo" of PC Algorithm Results, incl. Skeleton
pcAlgo.Perfect | PC-Algorithm [OLD]: Estimate Skeleton or Equivalence Class of a DAG
pcorOrder | Compute Partial Correlations
pcSelect | PC-Select: Estimate subgraph around a response variable
pcSelect.presel | Estimate Subgraph around a Response Variable using Preselection
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
plot-method | Class '"EssGraph"'
plot-method | Class '"ParDAG"' of Parametric Causal Models
plot-method | Class "fciAlgo" of FCI Algorithm Results
plot-method | Class "pcAlgo" of PC Algorithm Results, incl. Skeleton
plotAG | Plot partial ancestral graphs (PAG)
plotSG | Plot the subgraph around a Specific Node in a Graph Object
possAn | Find possible ancestors of given node(s).
possDe | Find possible descendants of given node(s).
possibleDe | [DEPRECATED] Find possible descendants on definite status paths.
print.fciAlgo | Class "fciAlgo" of FCI Algorithm Results
print.pcAlgo | Class "pcAlgo" of PC Algorithm Results, incl. Skeleton

## -- Q --

qreach | Compute Possible-D-SEP(x,G) of a node x in a PDAG G

## -- R --

r.gauss.pardag | Generate a Gaussian Causal Model Randomly
randDAG | Random DAG Generation
randomDAG | Generate a Directed Acyclic Graph (DAG) randomly
rfci | Estimate an RFCI-PAG using the RFCI Algorithm
rmvDAG | Generate Multivariate Data according to a DAG
rmvnorm.ivent | Simulate from a Gaussian Causal Model

## -- S --

Score-class | Virtual Class "Score"
searchAM | Search for certain nodes in a DAG/CPDAG/MAG/PAG
shd | Compute Structural Hamming Distance (SHD)
show-method | Class "fciAlgo" of FCI Algorithm Results
show-method | Class "pcAlgo" of PC Algorithm Results, incl. Skeleton
show.fci.amat | Types and Display of Adjacency Matrices in Package 'pcalg'
show.pc.amat | Types and Display of Adjacency Matrices in Package 'pcalg'
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 Algorithm
summary-method | Class "fciAlgo" of FCI Algorithm Results
summary-method | Class "pcAlgo" of PC Algorithm Results, incl. Skeleton

## -- T --

targets2mat | Conversion between an intervention matrix and a list of intervention targets
triple2numb | Utility for conservative and majority rule in PC and FCI
trueCov | Covariance matrix of a DAG.

## -- U --

udag2apag | Last step of RFCI algorithm: Transform partially oriented graph into RFCI-PAG
udag2pag | Last steps of FCI algorithm: Transform Final Skeleton into FCI-PAG
udag2pdag | Last PC Algorithm Step: Extend Object with Skeleton to Completed PDAG
udag2pdagRelaxed | Last PC Algorithm Step: Extend Object with Skeleton to Completed PDAG
udag2pdagSpecial | Last PC Algorithm Step: Extend Object with Skeleton to Completed PDAG

## -- V --

visibleEdge | Check visible edge.

## -- W --

wgtMatrix | Weight Matrix of a Graph, e.g., a simulated DAG

## -- Z --

zStat | Test Conditional Independence of Gaussians via Fisher's Z