print.BGGM

Mainly used to avoid a plethora of different print
functions that overcrowded the documentation in previous versions
of 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>.

Philippe Rast

BGGM

Bayesian Gaussian Graphical Models

Donald Williams

Joris Mulder

print.BGGM function

<dl><dt>x</dt>
<dd>An object of class <code>BGGM</code></dd>
<dt>...</dt>
<dd>currently ignored</dd></dl>

Arguments

Print method for BGGM objects — print.BGGM

<dl>

<dt>x</dt>
<dd>An object of class <code>BGGM</code></dd>


<dt>...</dt>
<dd>currently ignored</dd>

</dl>

print.BGGM: Print method for `BGGM` objects

Description

Usage

Arguments