Package: causaleffect 1.3.17
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:
causaleffect_1.3.17.tar.gz
causaleffect_1.3.17.zip(r-4.7)causaleffect_1.3.17.zip(r-4.6)causaleffect_1.3.17.zip(r-4.5)
causaleffect_1.3.17.tgz(r-4.6-any)causaleffect_1.3.17.tgz(r-4.5-any)
causaleffect_1.3.17.tar.gz(r-4.7-any)causaleffect_1.3.17.tar.gz(r-4.6-any)
causaleffect_1.3.17.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
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 from:ff6059fbd4. Checks:7 WARNING, 1 ERROR, 1 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | WARNING | 137 | ||
| source / vignettes | ERROR | 167 | ||
| linux-release-x86_64 | WARNING | 132 | ||
| macos-release-arm64 | WARNING | 148 | ||
| macos-oldrel-arm64 | WARNING | 145 | ||
| windows-devel | WARNING | 129 | ||
| windows-release | WARNING | 109 | ||
| windows-oldrel | WARNING | 83 | ||
| wasm-release | OK | 109 |
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 |
