GGMnonreg: Non-Regularized Gaussian Graphical Models
Estimate non-regularized Gaussian graphical models, Ising models,
and mixed graphical models. The current methods consist of multiple regression,
a non-parametric bootstrap <doi:10.1080/00273171.2019.1575716>, and Fisher z
transformed partial correlations <doi:10.1111/bmsp.12173>. Parameter uncertainty,
predictability, and network replicability <doi:10.31234/osf.io/fb4sa> are also implemented.
| Version: |
1.0.0 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
Rdpack, bestglm, GGally, network, sna, Matrix, poibin, parallel, doParallel, foreach, corpcor, psych, MASS, stats, methods, ggplot2, GGMncv |
| Suggests: |
qgraph |
| Published: |
2021-04-08 |
| Author: |
Donald Williams [aut, cre] |
| Maintainer: |
Donald Williams <drwwilliams at ucdavis.edu> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| Citation: |
GGMnonreg citation info |
| Materials: |
README |
| CRAN checks: |
GGMnonreg results |
Documentation:
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