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'; the package is temporarily unavailable on the CRAN repository; formerly available versions can be obtained from the archive), '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: 0.2.6.2
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: 2020-02-17
Author: Christina Heinze-Deml, Nicolai Meinshausen
Maintainer: Christina Heinze-Deml <heinzedeml at stat.math.ethz.ch>
BugReports: https://github.com/christinaheinze/CompareCausalNetworks/issues
License: GPL-2 | GPL-3 [expanded from: GPL]
URL: https://github.com/christinaheinze/CompareCausalNetworks
NeedsCompilation: no
Citation: CompareCausalNetworks citation info
In views: CausalInference
CRAN checks: CompareCausalNetworks results

Documentation:

Reference manual: CompareCausalNetworks.pdf

Downloads:

Package source: CompareCausalNetworks_0.2.6.2.tar.gz
Windows binaries: r-devel: CompareCausalNetworks_0.2.6.2.zip, r-release: CompareCausalNetworks_0.2.6.2.zip, r-oldrel: CompareCausalNetworks_0.2.6.2.zip
macOS binaries: r-release (arm64): CompareCausalNetworks_0.2.6.2.tgz, r-oldrel (arm64): CompareCausalNetworks_0.2.6.2.tgz, r-release (x86_64): CompareCausalNetworks_0.2.6.2.tgz
Old sources: CompareCausalNetworks archive

Reverse dependencies:

Reverse imports: SELF

Linking:

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