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PolyTree: Estimate Causal Polytree from Data

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) <doi:10.48550/arXiv.2209.07028>. The method is fully nonparametric, making no use of linearity assumptions, and especially useful when the number of variables is large.

Version: 0.0.1
Imports: FOCI, igraph
Published: 2024-03-25
DOI: 10.32614/CRAN.package.PolyTree
Author: Sourav Chatterjee ORCID iD [aut, cre]
Maintainer: Sourav Chatterjee <souravc at stanford.edu>
License: MIT + file LICENSE
NeedsCompilation: no
Citation: PolyTree citation info
CRAN checks: PolyTree results

Documentation:

Reference manual: PolyTree.pdf

Downloads:

Package source: PolyTree_0.0.1.tar.gz
Windows binaries: r-devel: PolyTree_0.0.1.zip, r-release: PolyTree_0.0.1.zip, r-oldrel: PolyTree_0.0.1.zip
macOS binaries: r-release (arm64): PolyTree_0.0.1.tgz, r-oldrel (arm64): PolyTree_0.0.1.tgz, r-release (x86_64): PolyTree_0.0.1.tgz, r-oldrel (x86_64): PolyTree_0.0.1.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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