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PFCI

0.1.1

Penalized Fast Causal Inference for High-Dimensional Structure Learning

0packages depend
705downloads / year
1.5%test coverage
13/13checks pass

Overview

About
Maintained by Dhrubajyoti GhoshFirst published 2026-06-022 releasesCRAN page ↗GitHub ↗

Implements Penalized Fast Causal Inference (PFCI), a two-stage causal structure learning procedure for high-dimensional settings with potential latent variables and selection bias. In the first stage, neighborhood selection via the Lasso constructs a sparse undirected skeleton. In the second stage, the Fast Causal Inference (FCI) algorithm orients edges on this reduced graph, producing a Partial Ancestral Graph (PAG) that accounts for latent confounders. The method is consistent under sparsity assumptions and substantially faster than standard FCI and RFCI in high dimensions. See Pal, Ghosh, and Yang (2025) doi:10.48550/arXiv.2507.00173 for the underlying theory.

Install

Health

CRAN checks
13OK
Slowest check: 1.3 min · r-oldrel-macos-x86_64
Code health
Yes
Tests · ratio 0.09
1.5%
Coverage · measured lines
100%
Documentation · exports
3
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-06-03
    6 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 130 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
17%
Documented parameters
100%
Return-value docs
100%
References docs
17%

Downloads

705
CRAN downloads in the past year
Rank #14,921 · ~2/day · ~59/mo
Daily download trend is not available in this view yet.
12530 days
70590 days
7051 year
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Also on11 r2u

Repository

Repository
0Stars
0Forks
0Open issues
0Open PRs
0Releases
Last activity 2026-06-21

Repository practices

Upstream repositoryBeta

5 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/djghosh1123/pfci on 2026-08-09.

Continuous integration (1)
GitHub Actions
CRAN release process (2)
cran-comments.mdCRAN-SUBMISSION
Docs source (1)
README.Rmd
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
9 external dependencies (excludes base and recommended)
Depends (0)
none
Imports (3)
statsglassomethods
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (3)
Maintainer (1)
Author, Maintainer
Authors (3)
Author, Maintainer
Author
Package Timeline

2 releases. Pick two to compare their code metrics. R releases are shown for context.

  • 0.1.1Latest
    2026-06-03 · current release · diff ↗
  • 0.1.0
    2026-06-02
  • R
    R 4.6.0 released · 2026-04-24

Package metadata

First published
2026-06-02
Total releases
2 / 1 yrs
License
MIT + file LICENSE OSI
Download size
not tracked yet
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("PFCI")
Ghosh, D., Pal, S., & Yang, S. (2026). PFCI: Penalized Fast Causal Inference for High-Dimensional Structure Learning (Version 0.1.1) [Computer software]. https://doi.org/10.32614/CRAN.package.PFCI

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for PFCI version 0.1.1 [Data set]. HJJB, LLC. Data release v2026-08-13. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-13, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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