Learn R Programming

causalDisco (version 1.0.1)

Tools for Causal Discovery on Observational Data

Description

Tools for causal structure learning from observational data, with emphasis on temporally ordered variables. The package implements the Temporal Peter–Clark (TPC) algorithm (Petersen, Osler & Ekstrøm, 2021; ), the Temporal Greedy Equivalence Search (TGES) algorithm (Larsen, Ekstrøm & Petersen, 2025; ) and Temporal Fast Causal Inference (TFCI). It provides a unified framework for specifying background knowledge, which can be incorporated into the implemented algorithms from the R packages 'bnlearn' (Scutari, 2010; ) and 'pcalg' (Kalish et al., 2012; ), as well as the Java library 'Tetrad' (Scheines et al., 1998; ). The package further includes utilities for visualization, comparison, and evaluation of graph structures, facilitating performance evaluation and methodological studies.

Copy Link

Version

Install

install.packages('causalDisco')

Monthly Downloads

308

Version

1.0.1

License

GPL-2

Issues

Pull Requests

Stars

Forks

Maintainer

Bjarke Hautop Kristensen

Last Published

February 24th, 2026

Functions in causalDisco (1.0.1)

PcalgSearch

R6 Interface to pcalg Search Algorithms
TetradSearch

R6 Interface to Tetrad Search Algorithms
add_tier

Add a Tier to Knowledge
CausalDiscoSearch

R6 Interface to causalDisco Search Algorithms
BnlearnSearch

R6 Interface to bnlearn Search Algorithms
TemporalBDeu-class

Temporal Bayesian Dirichlet equivalent uniform (Score criterion)
TemporalBIC-class

Temporal Bayesian Information Criterion (Score criterion)
add_exogenous

Add Exogenous Variables to Knowledge
add_vars

Add Variables to Knowledge
add_to_tier

Add Variables to a Tier in Knowledge
cat_ord_data

Simulated Ordered Categorical Data
as_bnlearn_knowledge

Convert Knowledge to bnlearn Knowledge
boss_fci

BOSS-FCI Algorithm for Causal Discovery
confusion

Confusion Matrix
causalDisco-package

causalDisco: Causal Discovery in R
as_pcalg_constraints

Convert Knowledge to pcalg Knowledge
as_tetrad_knowledge

Convert Knowledge to Tetrad Knowledge
boss

BOSS Algorithm for Causal Discovery
cat_data

Simulated Categorical Data
cat_data_mcar

Simulated Categorical Data with MCAR
evaluate

Evaluate Causal Graph Estimates
distribute_engine_args

Distribute and Validate Engine Arguments
deparse_knowledge

Deparse a Knowledge Object into Knowledge DSL Code
disco

Perform Causal Discovery
disco_algs_return_doc_dag

Causal Discovery Algorithm Return Value DAG
disco_algs_return_doc_pag

Causal Discovery Algorithm Return Value PAG
disco_algs_return_doc_pdag

Causal Discovery Algorithm Return Value PDAG
cor_test

Test for Vanishing Partial Correlations
convert_tiers_to_forbidden

Convert Tiered Knowledge to Forbidden Knowledge
forbid_edge

Add Forbidden Edges to Knowledge
g1_score

G1 score
disco_note

Disco Recommendation Note
install_tetrad

Install Tetrad GUI
fci

FCI Algorithm for Causal Discovery
ges

GES Algorithm for Causal Discovery
iamb-family

IAMB Family of Causal Discovery Algorithms
generate_dag_data

Generate Synthetic Data from a Linear Gaussian DAG
gs

GS Algorithm for Causal Discovery
knowledge

Define Background Knowledge
fdr

False Discovery Rate
gfci

GFCI Algorithm for Causal Discovery
get_tiers

Get Tiers from Knowledge
new_disco_method

Add a New causalDisco Method
mix_data

Simulated Mixed Data
npv

Negative Predictive Value
make_tikz

Generate TikZ Code from a Causal Graph
knowledge_to_caugi

Convert Knowledge to Caugi
num_data

Simulated Numerical Data
precision

Precision
print.Disco

Print a Disco Object
num_data_latent

Simulated Numerical Data with Latent Variable
pc

PC Algorithm for Causal Discovery
reg_test

Regression-based Information Loss Test
reexports

Objects exported from other packages
recall

Recall
print.Knowledge

Print a Knowledge Object
plot.Disco

Plot a Disco Object
plot.Knowledge

Plot a Knowledge Object
remove_tiers

Remove Tiers from Knowledge
f1_score

F1 score
remove_vars

Remove Variables from Knowledge
reposition_tier

Move a Tier Relative to Another in Knowledge
seq_tiers

Generate a Bundle of Tier–Variable Formulas
specificity

Specificity
summary.Disco

Summarize a Disco Object
reorder_tiers

Reorder Tiers in Knowledge
false_omission_rate

False Omission Rate
grasp

GRaSP Algorithm for Causal Discovery
set_knowledge

Set Background Knowledge to Disco Method
plot

Plot Method for causalDisco Objects
sp_fci

SP-FCI Algorithm for Causal Discovery
grasp_fci

GRaSP-FCI Algorithm for Causal Discovery
+.Knowledge

Merge Knowledge Objects
sim_dag

Simulate a Random DAG
tpc_example

Simulated Life-Course Data
tfci

TFCI Algorithm for Causal Discovery
summary.Knowledge

Summarize a Knowledge Object
tpc_run

Run the TPC Algorithm for Causal Discovery
register_tetrad_algorithm

Register a New Tetrad Algorithm
reset_tetrad_alg_registry

Reset the Tetrad Algorithm Registry
remove_edge

Remove an Edge from Knowledge
require_edge

Add Required Edges to Knowledge
tges

TGES Algorithm for Causal Discovery
tfci_run

Run the TFCI Algorithm for Causal Discovery
unfreeze

Unfreeze a Knowledge Object.
tpc

TPC Algorithm for Causal Discovery
tges_run

Run the TGES Algorithm for Causal Discovery
verify_tetrad

Check Tetrad Installation