Estimate Causal Polytree from Data
Overview
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.
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
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>.
- NOTE11 OK, 2 NOTENow
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 4
- Examples that run
- 100%1 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 25%
Downloads
Dependencies
Installing PolyTree adds 14 packages (10 with compiled code, 14 MB of source tarballs). Heaviest: data.table 5.7 MB, igraph 4.8 MB, vctrs 1.0 MB.
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 0.0.1Latest2024-03-25 · current release
- RR 4.3.0 released · 2023-04-21
Package metadata
- First published
- 2024-03-25
- Total releases
- 1 / 2 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 4.1 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("PolyTree")The package provides a citation file, so citation() returns the authors' own entry.
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