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), 'RFCI' (really fast causal inference) (all from package 'pcalg') and regression.

Version: 0.1.4
Depends: R (≥ 3.1.0)
Imports: Matrix, methods
Suggests: pcalg, InvariantCausalPrediction, glmnet, backShift, CAM, kernlab, mgcv, testthat
Published: 2015-10-07
Author: Christina Heinze, Nicolai Meinshausen
Maintainer: Christina Heinze <heinze at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
CRAN checks: CompareCausalNetworks results


Reference manual: CompareCausalNetworks.pdf
Package source: CompareCausalNetworks_0.1.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: CompareCausalNetworks_0.1.4.tgz, r-oldrel: CompareCausalNetworks_0.1.4.tgz
Old sources: CompareCausalNetworks archive


Please use the canonical form to link to this page.