Provides the selected graph based on credible intervals for the partial correlations that did not contain zero (Williams 2018) .
Usage
# S3 method for class 'estimate'
select(object, cred = 0.95, alternative = "two.sided", ...)
Arguments
- object
An object of class
estimate.default
.- cred
Numeric. The credible interval width for selecting the graph (defaults to 0.95; must be between 0 and 1).
- alternative
A character string specifying the alternative hypothesis. It must be one of "two.sided" (default), "greater" or "less". See note for futher details.
- ...
Currently ignored.
Value
The returned object of class select.estimate
contains a lot of information that
is used for printing and plotting the results. For users of BGGM, the following
are the useful objects:
pcor_adj
Selected partial correlation matrix (weighted adjacency).adj
Adjacency matrix for the selected edgesobject
An object of classestimate
(the fitted model).
Details
This package was built for the social-behavioral sciences in particular. In these applications, there is
strong theory that expects all effects to be positive. This is known as a "positive manifold" and
this notion has a rich tradition in psychometrics. Hence, this can be incorporated into the graph with
alternative = "greater"
. This results in the estimated structure including only positive edges.
References
Williams DR (2018). “Bayesian Estimation for Gaussian Graphical Models: Structure Learning, Predictability, and Network Comparisons.” arXiv. doi:10.31234/OSF.IO/X8DPR .
See also
estimate
and ggm_compare_estimate
for several examples.