PolyTree
Estimate Causal Polytree from Data
v0.0.1
·
Mar 25, 2024
·
MIT + file LICENSE
Description
Given a data matrix with rows representing data vectors and columns representing variables, produces a directed polytree for the underlying causal structure. Based on the algorithm developed in Chatterjee and Vidyasagar (2022) <arxiv:2209.07028>. The method is fully nonparametric, making no use of linearity assumptions, and especially useful when the number of variables is large.
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| Flavor | Status |
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| r-devel-linux-x86_64-debian-clang | NOTE |
| r-devel-linux-x86_64-debian-gcc | NOTE |
| r-devel-linux-x86_64-fedora-clang | OK |
| r-devel-linux-x86_64-fedora-gcc | OK |
| r-devel-macos-arm64 | OK |
| r-devel-windows-x86_64 | OK |
| r-oldrel-macos-arm64 | OK |
| r-oldrel-macos-x86_64 | OK |
| r-oldrel-windows-x86_64 | OK |
| r-patched-linux-x86_64 | OK |
| r-release-linux-x86_64 | OK |
| r-release-macos-arm64 | OK |
| r-release-macos-x86_64 | OK |
| r-release-windows-x86_64 | OK |
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CRAN incoming feasibility
Maintainer: ‘Sourav Chatterjee <souravc@stanford.edu>’ The Description field contains Vidyasagar (2022) <arxiv:2209.07028>. The method is fully Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
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r-devel-linux-x86_64-debian-gcc
CRAN incoming feasibility
Maintainer: ‘Sourav Chatterjee <souravc@stanford.edu>’ The Description field contains Vidyasagar (2022) <arxiv:2209.07028>. The method is fully Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE
r-devel-linux-x86_64-debian-clang
CRAN incoming feasibility
Maintainer: ‘Sourav Chatterjee <souravc@stanford.edu>’ The Description field contains Vidyasagar (2022) <arxiv:2209.07028>. The method is fully Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
NOTE
r-devel-linux-x86_64-debian-gcc
CRAN incoming feasibility
Maintainer: ‘Sourav Chatterjee <souravc@stanford.edu>’ The Description field contains Vidyasagar (2022) <arxiv:2209.07028>. The method is fully Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
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0.0.1
Mar 9, 2026