causalDisco: Causal Discovery in R

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; doi:10.1093/aje/kwab087 ), the Temporal Greedy Equivalence Search (TGES) algorithm (Larsen, Ekstrøm & Petersen, 2025; doi:10.48550/arXiv.2502.06232 ) 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; doi:10.18637/jss.v035.i03 ) and 'pcalg' (Kalish et al., 2012; doi:10.18637/jss.v047.i11 ), as well as the Java library 'Tetrad' (Scheines et al., 1998; doi:10.1207/s15327906mbr3301_3 ). The package further includes utilities for visualization, comparison, and evaluation of graph structures, facilitating performance evaluation and methodological studies.

System requirements (optional)

If you want to use algorithms from the Java library Tetrad, a Java JDK (>= 21) is required. The Tetrad .jar file can be downloaded using install_tetrad().

See also

Useful links:

• https://github.com/disco-coders/causalDisco

• https://disco-coders.github.io/causalDisco/

• Report bugs at https://github.com/disco-coders/causalDisco/issues

Author

Maintainer: Bjarke Hautop Kristensen bjarke.kristensen@sund.ku.dk

Authors:

• Frederik Fabricius-Bjerre frederik@fabriciusbjerre.dk

• Anne Helby Petersen ahpe@sund.ku.dk

Other contributors:

• Claus Thorn Ekstrøm ekstrom@sund.ku.dk [contributor]

• Tobias Ellegaard Larsen tobias.ellegaard@sund.ku.dk [contributor]