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), <arXiv:1501.01332>, to nonlinear settings. For more details, see C. Heinze-Deml, J. Peters and N. Meinshausen: 'Invariant Causal Prediction for Nonlinear Models', <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 |
| 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 |
| CRAN checks: | nonlinearICP results |
| Reference manual: | nonlinearICP.pdf |
| 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: nonlinearICP_0.1.2.1.tgz, r-oldrel: nonlinearICP_0.1.2.1.tgz |
| Old sources: | nonlinearICP archive |
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