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>.
|Date of publication||2017-02-22 23:23:34|
|Maintainer||Santtu Tikka <firstname.lastname@example.org>|
causal.effect: Identify a causal effect
causaleffect-package: Deriving Expressions of Joint Interventional Distributions...
generalize: Derive a transport formula for a causal effect between a...
get.expression: Get the expression of a probability object
meta.transport: Derive a transport formula for a causal effect between a...
parse.graphml: Prepare GraphML files for internal use
recover: Recover a causal effect from selection bias
transport: Derive a transport formula for a causal effect between two...
zzaux.effect: Identify a causal effect using surrogate experiments
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