Constraint-based causal discovery using the PC algorithm while accounting for a partial node ordering, for example a partial temporal ordering when the data were collected in different waves of a cohort study. Andrews RM, Foraita R, Didelez V, Witte J (2021) <doi:10.48550/arXiv.2108.13395> provide a guide how to use tpc to analyse cohort data.
| Version: | 1.0 | 
| Depends: | pcalg, R (≥ 3.5.0) | 
| Imports: | graph, graphics, methods, parallel, utils | 
| Suggests: | Rgraphviz, testthat (≥ 3.0.0) | 
| Published: | 2023-02-20 | 
| DOI: | 10.32614/CRAN.package.tpc | 
| Author: | Janine Witte [aut],
  Ronja Foraita | 
| Maintainer: | Ronja Foraita <foraita at leibniz-bips.de> | 
| BugReports: | https://github.com/bips-hb/tpc/issues | 
| License: | GPL (≥ 3) | 
| URL: | https://github.com/bips-hb/tpc | 
| NeedsCompilation: | no | 
| Materials: | README | 
| CRAN checks: | tpc results | 
| Reference manual: | tpc.html , tpc.pdf | 
| Package source: | tpc_1.0.tar.gz | 
| Windows binaries: | r-devel: tpc_1.0.zip, r-release: tpc_1.0.zip, r-oldrel: tpc_1.0.zip | 
| macOS binaries: | r-release (arm64): tpc_1.0.tgz, r-oldrel (arm64): tpc_1.0.tgz, r-release (x86_64): tpc_1.0.tgz, r-oldrel (x86_64): tpc_1.0.tgz | 
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