Linear non-Gaussian Acyclic Models (LiNGAM)
Class "ParDAG"
of Parametric Causal Models
Class "EssGraph"
Class "GaussL0penIntScore"
Class "GaussL0penObsScore"
Class "GaussParDAG"
of Gaussian Causal Models
Virtual Class "Score"
Add background knowledge to a CPDAG or PDAG
Compute adjustment sets for covariate adjustment.
Types and Display of Adjacency Matrices in Package 'pcalg'
Find Set Satisfying the Generalized Backdoor Criterion (GBC)
Compute set of intervention effects
Convert a DAG to a CPDAG
Test for d-separation in a DAG
Estimate a PAG by the FCI Algorithm
Check Consistency of Conditional Independence for a Triple of Nodes
Compare two graphs in terms of TPR, FPR and TDR
Class "fciAlgo" of FCI Algorithm Results
Compute set of intervention effects in a fast way
G square Test for (Conditional) Independence of Binary Variables
Convert a DAG with latent variables into a PAG
Convert a DAG to an Essential Graph
Find all Unshielded Triples in an Undirected Graph
Class "gAlgo"
G square Test for (Conditional) Independence of Discrete Variables
Test If Set Satisfies Generalized Adjustment Criterion (GAC)
Greedy DAG Search to Estimate Markov Equivalence Class of DAG
Plotting a pcAlgo object using the package igraph
Check for a DAG, CPDAG or a maximally oriented PDAG
Transform a PAG into a MAG in the Corresponding Markov Equivalence Class
Estimate the Equivalence Class of a DAG using the PC Algorithm
Plot the subgraph around a Specific Node in a Graph Object
Test Conditional Independence of Gaussians via Fisher's Z
Computing the correlation graph
Compute D-SEP(x,y,G)
Test for d-separation in a DAG
Find possible ancestors of given node(s).
Random DAG Generation
Generate a Directed Acyclic Graph (DAG) randomly
Graphical Model 5-Dim Binary Example Data
Graphical Model Discrete 5-Dim Example Data
Estimate Multiset of Possible Total Causal Effects
Graphical Model 8-Dimensional Gaussian Example Data
Graphical Model 7-dim IDA Data Examples
Conversion between an intervention matrix and a list of intervention
targets
Estimate a PAG by the FCI+ Algorithm
Iteration through a list of all combinations of choose(n,k)
Estimate Interventional Markov Equivalence Class of a DAG by GIES
Estimate Multiset of Possible Total Joint Effects
Multiset of Possible Total Causal Effects for Several Target Var.s
PC-Algorithm [OLD]: Estimate Skeleton or Equivalence Class of a DAG
PC-Select: Estimate subgraph around a response variable
Enumerate All DAGs in a Markov Equivalence Class
Extend a Partially Directed Acyclic Graph (PDAG) to a DAG
Simulate from a Gaussian Causal Model
Compute Structural Hamming Distance (SHD)
Covariance matrix of a DAG.
Last step of RFCI algorithm: Transform partially oriented graph into RFCI-PAG
Check if a 3-node-path is Legal
Utility for conservative and majority rule in PC and FCI
Class "pcAlgo" of PC Algorithm Results, incl. Skeleton
Estimate Final Skeleton in the FCI algorithm
Plot partial ancestral graphs (PAG)
Estimate an RFCI-PAG using the RFCI Algorithm
Generate Multivariate Data according to a DAG
Estimate the Markov equivalence class of a DAG using GES
Get the "graph" Part or Aspect of R Object
Graphical Model 8-Dimensional Interventional Gaussian Example Data
Latent Variable 4-Dim Graphical Model Data Example
Estimate Subgraph around a Response Variable using Preselection
Internal Pcalg Functions
Compute Possible-D-SEP(x,G) of a node x in a PDAG G
Generate a Gaussian Causal Model Randomly
Uniform Sampling of Directed Acyclic Graphs (DAG)
Check visible edge.
Compute (Large) Correlation Matrix
Transform the adjacency matrix from pcalg into a dagitty object
Compute Partial Correlations
Find possible descendants of given node(s).
Show Adjacency Matrix of pcAlgo object
Show Edge List of pcAlgo object
Last steps of FCI algorithm: Transform Final Skeleton into FCI-PAG
Last PC Algorithm Step: Extend Object with Skeleton to Completed PDAG
[DEPRECATED] Find possible descendants on definite status paths.
Estimate Interventional Markov Equivalence Class of a DAG
Estimate (Initial) Skeleton of a DAG using the PC / PC-Stable Algorithm
Weight Matrix of a Graph, e.g., a simulated DAG