select.estimate {BGGM} | R Documentation |
Graph Selection for estimate
Objects
Description
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 |
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. |
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.
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 edges -
object
An object of classestimate
(the fitted model).
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.
Examples
# note: iter = 250 for demonstrative purposes
# data
Y <- bfi[,1:10]
# estimate
fit <- estimate(Y, iter = 250,
progress = FALSE)
# select edge set
E <- select(fit)