pcalg v2.6-7


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Methods for Graphical Models and Causal Inference

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), the Generalized Adjustment Criterion (GAC) and some related functions are implemented. Functions for incorporating background knowledge are provided.

Functions in pcalg

Name Description
ParDAG-class Class "ParDAG" of Parametric Causal Models
addBgKnowledge Add background knowledge to a CPDAG or PDAG
Score-class Virtual Class "Score"
beta.special.pcObj Compute set of intervention effects in a fast way
fci Estimate a PAG by the FCI Algorithm
beta.special Compute set of intervention effects
adjustment Compute adjustment sets for covariate adjustment.
amatType Types and Display of Adjacency Matrices in Package 'pcalg'
backdoor Find Set Satisfying the Generalized Backdoor Criterion (GBC)
dag2pag Convert a DAG with latent variables into a PAG
gds Greedy DAG Search to Estimate Markov Equivalence Class of DAG
dag2essgraph Convert a DAG to an Essential Graph
EssGraph-class Class "EssGraph"
ages Estimate an APDAG within the Markov equivalence class of a DAG using AGES
GaussL0penIntScore-class Class "GaussL0penIntScore"
find.unsh.triple Find all Unshielded Triples in an Undirected Graph
gmD Graphical Model Discrete 5-Dim Example Data
fciPlus Estimate a PAG by the FCI+ Algorithm
optAdjSet Compute the optimal adjustment set
gies Estimate Interventional Markov Equivalence Class of a DAG by GIES
legal.path Check if a 3-node-path is Legal
fciAlgo-class Class "fciAlgo" of FCI Algorithm Results
gmG Graphical Model 8-Dimensional Gaussian Example Data
mat2targets Conversion between an intervention matrix and a list of intervention targets
gmB Graphical Model 5-Dim Binary Example Data
ges Estimate the Markov equivalence class of a DAG using GES
pag2mag Transform a PAG into a MAG in the Corresponding Markov Equivalence Class
gmI Graphical Model 7-dim IDA Data Examples
mcor Compute (Large) Correlation Matrix
gmInt Graphical Model 8-Dimensional Interventional Gaussian Example Data
GaussParDAG-class Class "GaussParDAG" of Gaussian Causal Models
dsep Test for d-separation in a DAG
binCItest G square Test for (Conditional) Independence of Binary Variables
checkTriple Check Consistency of Conditional Independence for a Triple of Nodes
GaussL0penObsScore-class Class "GaussL0penObsScore"
pcalg-internal Internal Pcalg Functions
opt.target Get an optimal intervention target
pcalg2dagitty Transform the adjacency matrix from pcalg into a dagitty object
pdag2dag Extend a Partially Directed Acyclic Graph (PDAG) to a DAG
possDe Find possible descendants of given node(s).
wgtMatrix Weight Matrix of a Graph, e.g., a simulated DAG
r.gauss.pardag Generate a Gaussian Causal Model Randomly
possAn Find possible ancestors of given node(s).
randDAG Random DAG Generation
gAlgo-class Class "gAlgo"
corGraph Computing the correlation graph
dag2cpdag Convert a DAG to a CPDAG
dsepTest Test for d-separation in a DAG
pdsep Estimate Final Skeleton in the FCI algorithm
disCItest G square Test for (Conditional) Independence of Discrete Variables
trueCov Covariance matrix of a DAG.
skeleton Estimate (Initial) Skeleton of a DAG using the PC / PC-Stable Algorithm
pcSelect PC-Select: Estimate subgraph around a response variable
iplotPC Plotting a pcAlgo object using the package igraph
idaFast Multiset of Possible Total Causal Effects for Several Target Var.s
dreach Compute D-SEP(x,y,G)
gac Test If Set Satisfies Generalized Adjustment Criterion (GAC)
isValidGraph Check for a DAG, CPDAG or a maximally oriented PDAG
pc Estimate the Equivalence Class of a DAG using the PC Algorithm
jointIda Estimate Multiset of Possible Total Joint Effects
pc.cons.intern Utility for conservative and majority rule in PC and FCI
plotAG Plot partial ancestral graphs (PAG)
shd Compute Structural Hamming Distance (SHD)
pcSelect.presel Estimate Subgraph around a Response Variable using Preselection
showAmat Show Adjacency Matrix of pcAlgo object
plotSG Plot the subgraph around a Specific Node in a Graph Object
udag2apag Last step of RFCI algorithm: Transform partially oriented graph into RFCI-PAG
randomDAG Generate a Directed Acyclic Graph (DAG) randomly
udag2pag Last steps of FCI algorithm: Transform Final Skeleton into FCI-PAG
rmvnorm.ivent Simulate from a Gaussian Causal Model
rmvDAG Generate Multivariate Data according to a DAG
visibleEdge Check visible edge.
udag2pdag Last PC Algorithm Step: Extend Object with Skeleton to Completed PDAG
getGraph Get the "graph" Part or Aspect of R Object
pcAlgo-class Class "pcAlgo" of PC Algorithm Results, incl. Skeleton
ida Estimate Multiset of Possible Joint Total Causal Effects
getNextSet Iteration through a list of all combinations of choose(n,k)
gmL Latent Variable 4-Dim Graphical Model Data Example
rfci Estimate an RFCI-PAG using the RFCI Algorithm
pcAlgo PC-Algorithm [OLD]: Estimate Skeleton or Equivalence Class of a DAG
pdag2allDags Enumerate All DAGs in a Markov Equivalence Class
pcorOrder Compute Partial Correlations
possibleDe [DEPRECATED] Find possible descendants on definite status paths.
qreach Compute Possible-D-SEP(x,G) of a node x in a PDAG G
simy Estimate Interventional Markov Equivalence Class of a DAG
showEdgeList Show Edge List of pcAlgo object
LINGAM Linear non-Gaussian Acyclic Models (LiNGAM)
condIndFisherZ Test Conditional Independence of Gaussians via Fisher's Z
compareGraphs Compare two graphs in terms of TPR, FPR and TDR
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Last month downloads


Date 2019-10-20
LinkingTo Rcpp (>= 0.11.0), RcppArmadillo, BH
ByteCompile yes
NeedsCompilation yes
Encoding UTF-8
License GPL (>= 2)
URL http://pcalg.r-forge.r-project.org/
RoxygenNote 6.1.1
Packaged 2019-10-23 10:20:32 UTC; kalischm
Repository CRAN
Date/Publication 2019-10-23 14:40:02 UTC

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