psychnets: Tidy Clean-Room Psychological Network Modeling
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.
| Version: |
0.5.2 |
| 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 |
| Published: |
2026-08-23 |
| DOI: |
10.32614/CRAN.package.psychnets |
| Author: |
Mohammed Saqr [aut, cre, cph],
Sonsoles López-Pernas [aut] |
| Maintainer: |
Mohammed Saqr <saqr at saqr.me> |
| BugReports: |
https://github.com/mohsaqr/psychnets/issues |
| License: |
GPL-3 |
| URL: |
https://pak.dynasite.org/psychnets,
https://github.com/mohsaqr/psychnets |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
psychnets results |
Documentation:
Downloads:
Reverse dependencies:
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