dosearch-package

Solves causal effect identifiability problems from arbitrary
observational and experimental distributions using a heuristic search.
Allows for the presence of advanced data-generating mechanisms.
See Tikka et al. (2021) <a href="/link/doi%3A10.18637%2Fjss.v099.i05?package=dosearch&version=1.0.11" data-mini-rdoc="dosearch::doi:10.18637/jss.v099.i05">doi:10.18637/jss.v099.i05</a> for further details.

Identification of causal effects from arbitrary observational and
experimental probability distributions via do-calculus and standard
probability manipulations using a search-based algorithm by
Tikka, Hyttinen and Karvanen (2021) <doi:10.18637/jss.v099.i05>.
Allows for the presence of mechanisms related to selection bias
(Bareinboim and Tian, 2015) <doi:10.1609/aaai.v29i1.9679>,
transportability (Bareinboim and Pearl, 2014)
<http://ftp.cs.ucla.edu/pub/stat_ser/r443.pdf>,
missing data (Mohan, Pearl, and Tian, 2013)
<http://ftp.cs.ucla.edu/pub/stat_ser/r410.pdf>) and arbitrary combinations
of these. Also supports identification in the presence of context-specific
independence (CSI) relations through labeled directed acyclic graphs
(LDAG). For details on CSIs see (Corander et al., 2019)
<doi:10.1016/j.apal.2019.04.004>.

Santtu Tikka

dosearch

Causal Effect Identification from Multiple Incomplete Data
Sources

Antti Hyttinen

Juha Karvanen

dosearch-package function

Santtu Tikka, Antti Hyttinen, Juha Karvanen

Author

Solves causal effect identifiability problems from arbitrary
observational and experimental distributions using a heuristic search.
Allows for the presence of advanced data-generating mechanisms.
See Tikka et al. (2021) <a href='doi:10.18637/jss.v099.i05'>doi:10.18637/jss.v099.i05</a> for further details.

dosearch-package: Causal Effect Identification from Multiple Incomplete Data Sources

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References

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