Tools for Causal Discovery on Observational Data

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Documentation for package ‘causalDisco’ version 0.9.1

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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