BGGM

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) doi:10.31234/osf.io/x8dpr, Williams and Mulder (2019) doi:10.31234/osf.io/ypxd8, Williams, Rast, Pericchi, and Mulder (2019) doi:10.31234/osf.io/yt386.

Last 30 days

This package has been downloaded 627 times in the last 30 days. More downloads than an obscure whitepaper, but not enough to bring down any servers. A solid effort! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 20 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 39,458 times in the last 365 days. The academic equivalent of having a dedicated subreddit. There are fans, and maybe even a few trolls! The day with the most downloads was Apr 28, 2024 with 927 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.