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.
Package details |
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Maintainer | Donald Williams <drwwilliams@ucdavis.edu> |
License | GPL-2 |
Version | 1.1.0 |
Package repository | View on GitHub |
Installation |
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