nonlinearICP: Invariant Causal Prediction for Nonlinear Models

Performs 'nonlinear Invariant Causal Prediction' to estimate the causal parents of a given target variable from data collected in different experimental or environmental conditions, extending 'Invariant Causal Prediction' from Peters, Buehlmann and Meinshausen (2016), <doi:10.48550/arXiv.1501.01332>, to nonlinear settings. For more details, see C. Heinze-Deml, J. Peters and N. Meinshausen: 'Invariant Causal Prediction for Nonlinear Models', <doi:10.48550/arXiv.1706.08576>.

Depends: R (≥ 3.1.0)
Imports: methods, CondIndTests, data.tree, caTools, randomForest
Suggests: testthat
Published: 2017-07-31
DOI: 10.32614/CRAN.package.nonlinearICP
Author: Christina Heinze-Deml, Jonas Peters
Maintainer: Christina Heinze-Deml <heinzedeml at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
Citation: nonlinearICP citation info
In views: CausalInference
CRAN checks: nonlinearICP results


Reference manual: nonlinearICP.pdf


Package source: nonlinearICP_0.1.2.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): nonlinearICP_0.1.2.1.tgz, r-oldrel (arm64): nonlinearICP_0.1.2.1.tgz, r-release (x86_64): nonlinearICP_0.1.2.1.tgz, r-oldrel (x86_64): nonlinearICP_0.1.2.1.tgz
Old sources: nonlinearICP archive


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