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PFCI  

Penalized Fast Causal Inference for High-Dimensional Structure Learning
View on CRAN: Click here


Download and install PFCI package within the R console
Install from CRAN:
install.packages("PFCI")

Install from Github:
library("remotes")
install_github("cran/PFCI")

Install by package version:
library("remotes")
install_version("PFCI", "0.1.1")



Attach the package and use:
library("PFCI")
Maintained by
Dhrubajyoti Ghosh
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-02
Latest Update: 2026-06-03
Description:
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.
How to cite:
Dhrubajyoti Ghosh (2026). PFCI: Penalized Fast Causal Inference for High-Dimensional Structure Learning. R package version 0.1.1, https://cran.r-project.org/web/packages/PFCI. Accessed 24 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:16), 0.1.0 (2026-06-02 13:20)
Other packages that cited PFCI R package
View PFCI citation profile
Other R packages that PFCI depends, imports, suggests or enhances
Complete documentation for PFCI
Functions, R codes and Examples using the PFCI R package
Full PFCI package functions and examples
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