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.

Documentation

Manual: CompareCausalNetworks.pdf
Vignette: None available.

Maintainer: Christina Heinze-Deml <heinzedeml at stat.math.ethz.ch>

Author(s): Christina Heinze-Deml <heinzedeml at stat.math.ethz.ch>, Nicolai Meinshausen <meinshausen at stat.math.ethz.ch>

Install package and any missing dependencies by running this line in your R console:

install.packages("CompareCausalNetworks")

Depends R (>= 3.1.0)
Imports Matrix, methods
Suggests pcalg, InvariantCausalPrediction, glmnet, backShift, CAM, kernlab, mgcv, testthat
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Package CompareCausalNetworks
Materials
URL https://github.com/christinaheinze/CompareCausalNetworks
Task Views
Version 0.1.5
Published 2016-12-01
License GPL
BugReports https://github.com/christinaheinze/CompareCausalNetworks/issues
SystemRequirements
NeedsCompilation no
Citation
CRAN checks CompareCausalNetworks check results
Package source CompareCausalNetworks_0.1.5.tar.gz