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>.

Version:	0.1.2.1
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 stat.math.ethz.ch>
BugReports:	https://github.com/christinaheinze/nonlinearICP-and-CondIndTests/issues
License:	GPL-2 | GPL-3 [expanded from: GPL]
URL:	https://github.com/christinaheinze/nonlinearICP-and-CondIndTests
NeedsCompilation:	no
Citation:	nonlinearICP citation info
In views:	CausalInference
CRAN checks:	nonlinearICP results

Documentation:

Reference manual:

nonlinearICP.pdf

Downloads:

Package source:	nonlinearICP_0.1.2.1.tar.gz
Windows binaries:	r-devel: nonlinearICP_0.1.2.1.zip, r-release: nonlinearICP_0.1.2.1.zip, r-oldrel: nonlinearICP_0.1.2.1.zip
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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