Package: nonlinearICP 0.1.2.1
Christina Heinze-Deml
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), <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>.
Authors:
nonlinearICP_0.1.2.1.tar.gz
nonlinearICP_0.1.2.1.zip(r-4.7)nonlinearICP_0.1.2.1.zip(r-4.6)nonlinearICP_0.1.2.1.zip(r-4.5)
nonlinearICP_0.1.2.1.tgz(r-4.6-any)nonlinearICP_0.1.2.1.tgz(r-4.5-any)
nonlinearICP_0.1.2.1.tar.gz(r-4.7-any)nonlinearICP_0.1.2.1.tar.gz(r-4.6-any)
nonlinearICP_0.1.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
nonlinearICP/json (API)
| # Install 'nonlinearICP' in R: |
| install.packages('nonlinearICP', repos = c('https://christinaheinze.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/christinaheinze/nonlinearicp-and-condindtests/issues
- simData - Example dataset for tests
Last updated from:e6808046f2. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 199 | ||
| source / vignettes | OK | 221 | ||
| linux-release-x86_64 | OK | 203 | ||
| macos-release-arm64 | OK | 251 | ||
| macos-oldrel-arm64 | OK | 337 | ||
| windows-devel | OK | 250 | ||
| windows-release | OK | 278 | ||
| windows-oldrel | OK | 292 | ||
| wasm-release | OK | 104 |
Exports:nonlinearICPvarSelectionRF
Dependencies:bitopsbootcaToolscodetoolsCondIndTestsdata.treeforeachglmnetiteratorsKendallkernlablatticelawstatMASSMatrixmgcvmizemvtnormnlmepracmaquantregForestR6randomForestrbibutilsRColorBrewerRcppRcppEigenRdpackRPtestsshapestringisurvival
