Package: psychnets
Title: Tidy Clean-Room Psychological Network Modeling
Version: 0.4.3
Authors@R: 
    c(person("Mohammed", "Saqr", email = "saqr@saqr.me",
             role = c("aut", "cre", "cph")),
      person("Sonsoles", "López-Pernas", role = "aut"))
Description: Provides clean-room implementations for estimating psychometric
    network models, including correlation and partial-correlation networks,
    Gaussian graphical models with extended Bayesian information criterion
    (EBIC) regularization, nonparanormal and stepwise selection variants,
    information-filtering networks (the triangulated maximally filtered graph
    and the local-global inverse covariance), relative-importance networks,
    and Ising and mixed graphical models
    <doi:10.3758/s13428-017-0862-1> <doi:10.1007/978-3-031-54464-4_19>. All
    methods are implemented from first principles in base R without compiled
    dependencies and return consistent, tidy outputs. Functions are designed
    to be transparent and report optimization diagnostics where applicable. For
    Gaussian graphical models, the graphical lasso stationarity
    (Karush-Kuhn-Tucker) residual quantifies the deviation of the estimated
    solution from the optimum of the corresponding convex optimization problem.
License: GPL-3
URL: https://pak.dynasite.org/psychnets,
        https://github.com/mohsaqr/psychnets
BugReports: https://github.com/mohsaqr/psychnets/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
Depends: R (>= 3.5.0)
Imports: grDevices, graphics, parallel, stats
Suggests: cocor, cograph, glasso, glmnet, igraph, IsingFit, knitr, mgm,
        mvtnorm, networktools, psych, qgraph, rmarkdown, testthat (>=
        3.0.0), tna
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-07-22 06:13:14 UTC; mohammedsaqr
Author: Mohammed Saqr [aut, cre, cph],
  Sonsoles López-Pernas [aut]
Maintainer: Mohammed Saqr <saqr@saqr.me>
Repository: CRAN
Date/Publication: 2026-07-30 17:20:02 UTC
