Man pages for causalDisco
Tools for Causal Discovery on Observational Data
| adj_confusion | Compute confusion matrix for comparing two adjacency matrices |
| as.graphNEL | Convert adjacency matrix to graphNEL object |
| average_degree | Compute average degree for adjacency matrix |
| compare | Compare two tpdag or tskeleton objects |
| confusion | Compute confusion matrix for comparing two adjacency matrices |
| corTest | Test for vanishing partial correlations |
| dir_confusion | Compute confusion matrix for comparing two adjacency matrices |
| edges | List of edges in adjacency matrix |
| essgraph2amat | Convert essential graph to adjacency matrix |
| evaluate | Evaluate adjacency matrix estimation |
| evaluate.array | Evaluate adjacency matrix estimation |
| evaluate.matrix | Evaluate adjacency matrix estimation |
| evaluate.tamat | Evaluate adjacency matrix estimation |
| F1 | F1 score |
| FDR | False Discovery Rate |
| FOR | False Omission Rate |
| G1 | G1 score |
| gausCorScore | Gaussian L0 score computed on correlation matrix |
| graph2amat | Convert graphNEL object to adjacency matrix |
| is_cpdag | Check for CPDAG |
| is_pdag | Check for PDAG |
| maketikz | Generate Latex tikz code for plotting a temporal DAG or PDAG. |
| maxnedges | Compute maximal number of edges for graph |
| nDAGs | Number of different DAGs |
| nedges | Number of edges in adjacency matrix |
| NPV | Negative predictive value |
| plot.tamat | Plot adjacency matrix with order information |
| plotTempoMech | Plot temporal data generating mechanism |
| plot.tpdag | Plot temporal partially directed acyclic graph (TPDAG) |
| plot.tskeleton | Plot temporal skeleton |
| precision | Precision |
| probmat2amat | Convert a matrix of probabilities into an adjacency matrix |
| recall | Recall |
| regTest | Regression-based information loss test |
| shd | Structural hamming distance between adjacency matrices |
| simDAG | Simulate a random DAG |
| simGausFromDAG | Simulate Gaussian data according to DAG |
| specificity | Specificity |
| tamat | Make a temporal adjacency matrix |
| tpc | Perform causal discovery using the temporal PC algorithm... |
| tpcExample | Simulated data example |
