Tools for Causal Discovery on Observational Data

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Documentation for package ‘causalDisco’ version 0.9.1

• DESCRIPTION file.
• Package NEWS.

Help Pages

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
plot.tpdag	Plot temporal partially directed acyclic graph (TPDAG)
plot.tskeleton	Plot temporal skeleton
plotTempoMech	Plot temporal data generating mechanism
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 (TPC)
tpcExample	Simulated data example