Tools for Causal Discovery on Observational Data

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.


Reference manual

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install.packages("causalDisco")

1.2.1 by Bjarke Hautop Kristensen, 3 months ago


https://github.com/disco-coders/causalDisco, https://disco-coders.github.io/causalDisco/


Report a bug at https://github.com/disco-coders/causalDisco/issues


Browse source code at https://github.com/cran/causalDisco


Authors: Bjarke Hautop Kristensen [aut, cre] , Frederik Fabricius-Bjerre [aut] , Anne Helby Petersen [aut] , Claus Thorn Ekstrøm [aut] , Tobias Ellegaard Larsen [ctb]


Documentation:   PDF Manual  


GPL-2 license


Imports bnlearn, caugi, checkmate, cli, digest, dplyr, lifecycle, methods, pcalg, purrr, R6, rlang, S7, tibble, tidyr, tidyselect

Suggests knitr, mockery, quarto, RhpcBLASctl, rJava, rmarkdown, spelling, testthat, withr, mice, micd


See at CRAN