BGGM (1.0.0)

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Bayesian Gaussian Graphical Models.

Fit Bayesian Gaussian graphical models. The methods are separated into two Bayesian approaches for inference: hypothesis testing and estimation. There are extensions for confirmatory hypothesis testing, comparing Gaussian graphical models, and node wise predictability. These methods were recently introduced in the Gaussian graphical model literature, including Williams (2019) , Williams and Mulder (2019) , Williams, Rast, Pericchi, and Mulder (2019) .

Maintainer: Donald Williams
Author(s): Donald Williams [aut, cre], Joris Mulder [aut]

License: GPL-2

Uses: bayesplot, cowplot, doParallel, foreach, GGally, ggplot2, ggridges, MASS, Matrix, mvnfast, mvtnorm, network, pracma, reshape, reshape2, shiny, sna, stringr, knitr, dplyr, rmarkdown

Released 16 days ago.



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