dosearch: Causal Effect Identification from Multiple Incomplete Data
Sources
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>.
| Version: |
1.0.10 |
| Depends: |
R (≥ 4.0) |
| Imports: |
Rcpp |
| LinkingTo: |
Rcpp |
| Suggests: |
covr, dagitty, DiagrammeR, DOT, igraph, knitr, mockr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2024-07-09 |
| DOI: |
10.32614/CRAN.package.dosearch |
| Author: |
Santtu Tikka 
[aut, cre],
Antti Hyttinen
[ctb],
Juha Karvanen
[ctb] |
| Maintainer: |
Santtu Tikka <santtuth at gmail.com> |
| BugReports: |
https://github.com/santikka/dosearch/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/santikka/dosearch |
| NeedsCompilation: |
yes |
| Citation: |
dosearch citation info |
| Materials: |
NEWS |
| In views: |
CausalInference, MissingData |
| CRAN checks: |
dosearch results |
Documentation:
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