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 |
| Reference manual: | GGMnonreg.pdf |
| Package source: | GGMnonreg_1.0.0.tar.gz |
| Windows binaries: | r-devel: GGMnonreg_1.0.0.zip, r-release: GGMnonreg_1.0.0.zip, r-oldrel: GGMnonreg_1.0.0.zip |
| macOS binaries: | r-release (arm64): GGMnonreg_1.0.0.tgz, r-release (x86_64): GGMnonreg_1.0.0.tgz, r-oldrel: GGMnonreg_1.0.0.tgz |
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