select.estimate {BGGM} | R Documentation |
estimate
ObjectsProvides the selected graph based on credible intervals for the partial correlations that did not contain zero (Williams 2018).
## S3 method for class 'estimate'
select(object, cred = 0.95, alternative = "two.sided", ...)
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. |
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.
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 class estimate
(the fitted model).
Williams DR (2018). “Bayesian Estimation for Gaussian Graphical Models: Structure Learning, Predictability, and Network Comparisons.” arXiv. doi:10.31234/OSF.IO/X8DPR.
estimate
and ggm_compare_estimate
for several 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)