Package: causaleffect 1.3.16
causaleffect: Deriving Expressions of Joint Interventional Distributions and Transport Formulas in Causal Models
Functions for identification and transportation of causal effects. Provides a conditional causal effect identification algorithm (IDC) by Shpitser, I. and Pearl, J. (2006) <http://ftp.cs.ucla.edu/pub/stat_ser/r329-uai.pdf>, an algorithm for transportability from multiple domains with limited experiments by Bareinboim, E. and Pearl, J. (2014) <http://ftp.cs.ucla.edu/pub/stat_ser/r443.pdf>, and a selection bias recovery algorithm by Bareinboim, E. and Tian, J. (2015) <http://ftp.cs.ucla.edu/pub/stat_ser/r445.pdf>. All of the previously mentioned algorithms are based on a causal effect identification algorithm by Tian , J. (2002) <http://ftp.cs.ucla.edu/pub/stat_ser/r309.pdf>.
Authors:
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causaleffect.pdf |causaleffect.html✨
causaleffect/json (API)
NEWS
# Install 'causaleffect' in R: |
install.packages('causaleffect', repos = c('https://santikka.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/santikka/causaleffect/issues
causal-inferencecausal-modelscausality-algorithmsdirected-acyclic-graphgraphsidentifiabilityidentificationigraph
Last updated 2 years agofrom:78810a82c6. Checks:ERROR: 1 WARNING: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | FAIL | Nov 14 2024 |
R-4.5-win | WARNING | Nov 14 2024 |
R-4.5-linux | WARNING | Nov 14 2024 |
R-4.4-win | WARNING | Nov 14 2024 |
R-4.4-mac | WARNING | Nov 14 2024 |
R-4.3-win | WARNING | Nov 14 2024 |
R-4.3-mac | WARNING | Nov 14 2024 |
Exports:aux.effectcausal.effectgeneralizeget.expressionmeta.transportparse.graphmlrecoversurrogate.outcometransportverma.constraints
Dependencies:clicpp11glueigraphlatticelifecyclemagrittrMatrixpkgconfigrlangvctrs
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Deriving Expressions of Joint Interventional Distributions and Transport Formulas in Causal Models | causaleffect-package causaleffect |
Identify a causal effect using surrogate experiments | aux.effect |
Identify a causal effect | causal.effect |
Derive a transport formula for a causal effect between a target domain and multiple source domains with limited experiments | generalize |
Get the expression of a probability object | get.expression |
Derive a transport formula for a causal effect between a target domain and multiple source domains | meta.transport |
Prepare GraphML files for internal use | parse.graphml |
Recover a causal effect from selection bias | recover |
Derive a formula for a causal effect using surrogate outcomes | surrogate.outcome |
Derive a transport formula for a causal effect between two domains | transport |
Find Verma constraints for a given graph | verma.constraints |