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