B C D E F G I J L M P Q R S T U V W Z
| backdoor | Find Set Satisfying the Generalized Backdoor Criterion |
| 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 |
| causalEffect | Estimate Multiset of Possible Total Causal Effects |
| checkTriple | Check Consistency of Conditional Independence for a Triple of Nodes |
| 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 Variables |
| 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"' |
| 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 |
| ida | Estimate Multiset of Possible Total Causal Effects |
| idaFast | Multiset of Possible Total Causal Effects for Several Target Var.s |
| 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 Additive Models (LiNGAM) |
| local.mle-method | Class '"GaussL0penIntScore"' |
| local.mle-method | Class '"GaussL0penObsScore"' |
| local.score-method | Class '"GaussL0penIntScore"' |
| local.score-method | Class '"GaussL0penObsScore"' |
| mat2targets | Construct a list of intervention targets and a target index vector |
| mcor | Compute (Large) Correlation Matrix |
| 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 |
| pcAlgo | PC-Algorithm [OLD]: Estimate Skeleton or Equivalence Class of a DAG |
| pcAlgo-class | Class "pcAlgo" of PC Algorithm Results |
| 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 |
| 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 |
| 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. |
| print.fciAlgo | Class "fciAlgo" of FCI Algorithm Results |
| qreach | Compute Possible-D-SEP(x,G) of a node x in a PDAG G |
| 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 |
| Score-class | Virtual Class "Score" |
| shd | Compute Structural Hamming Distance (SHD) |
| show-method | Class "fciAlgo" of FCI Algorithm Results |
| show-method | Class "pcAlgo" of PC Algorithm Results |
| 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 |
| triple2numb | Utility for conservative and majority rule in PC and FCI |
| trueCov | Covariance matrix of a DAG. |
| 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 |
| unifDAG | Uniform Sampling of Directed Acyclic Graphs (DAG) |
| unifDAG.approx | Uniform Sampling of Directed Acyclic Graphs (DAG) |
| visibleEdge | Check visible edge. |
| wgtMatrix | Weight Matrix of a Graph, e.g., a simulated DAG |
| zStat | Test Conditional Independence of Gaussians via Fisher's Z |