Package: PFCI
Title: Penalized Fast Causal Inference for High-Dimensional Structure
        Learning
Version: 0.1.1
Date: 2026-05-28
Authors@R: c(
    person("Samhita", "Pal", email = "spal4@ncsu.edu",
           role = c("aut"), comment = c(ORCID = "0009-0001-4930-916X")),
    person("Dhrubajyoti", "Ghosh", email = "dghosh3@kennesaw.edu",
           role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3360-3786")),
    person("Shu", "Yang", email = "syang24@ncsu.edu",
           role = c("aut"), comment = c(ORCID = "0000-0001-7703-707X"))       
    )
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), accepted for publication in the Annals of
        Applied Statistics, <doi:10.48550/arXiv.2507.00173>, for the
        underlying theory.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/djghosh1123/PFCI
BugReports: https://github.com/djghosh1123/PFCI/issues
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
Imports: stats, glasso, methods
Suggests: pcalg, graph, RBGL, Rgraphviz, testthat (>= 3.0.0), knitr,
        rmarkdown, spelling
VignetteBuilder: knitr
Config/testthat/edition: 3
Language: en-US
Repository: https://djghosh1123.r-universe.dev
Date/Publication: 2026-06-21 14:58:54 UTC
RemoteUrl: https://github.com/djghosh1123/PFCI
RemoteRef: main
RemoteSha: 352f48121ca74d95b12487331e666de8ddb610f8
NeedsCompilation: no
Packaged: 2026-10-19 08:39:14 UTC; root
Author: Samhita Pal [aut] (ORCID: <https://orcid.org/0009-0001-4930-916X>),
  Dhrubajyoti Ghosh [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-3360-3786>),
  Shu Yang [aut] (ORCID: <https://orcid.org/0000-0001-7703-707X>)
Maintainer: Dhrubajyoti Ghosh <dghosh3@kennesaw.edu>