CompareCausalNetworks: Interface to Diverse Estimation Methods of Causal Networks

Unified interface for the estimation of causal networks, including the methods 'backShift' (from package 'backShift'), 'bivariateANM' (bivariate additive noise model), 'bivariateCAM' (bivariate causal additive model), 'CAM' (causal additive model) (from package 'CAM'), 'hiddenICP' (invariant causal prediction with hidden variables), 'ICP' (invariant causal prediction) (from package 'InvariantCausalPrediction'), 'GES' (greedy equivalence search), 'GIES' (greedy interventional equivalence search), 'LINGAM', 'PC' (PC Algorithm), 'FCI' (fast causal inference), 'RFCI' (really fast causal inference) (all from package 'pcalg') and regression.

Version: 0.2.2
Depends: R (≥ 3.1.0)
Imports: methods, Matrix, expm, data.table
Suggests: pcalg, InvariantCausalPrediction, glmnet, backShift, CAM, kernlab, mgcv, mboost, bnlearn, testthat, huge, flare
Published: 2018-05-18
Author: Christina Heinze-Deml, Nicolai Meinshausen
Maintainer: Christina Heinze-Deml <heinzedeml at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
Citation: CompareCausalNetworks citation info
CRAN checks: CompareCausalNetworks results


Reference manual: CompareCausalNetworks.pdf
Package source: CompareCausalNetworks_0.2.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: CompareCausalNetworks_0.2.2.tgz, r-oldrel: CompareCausalNetworks_0.2.2.tgz
Old sources: CompareCausalNetworks archive

Reverse dependencies:

Reverse imports: SELF


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