get_centrality {tsnet} | R Documentation |
Compute Centrality Measures
Description
This function computes various network centrality measures for a given GVAR
fit object. Centrality measures describe the "connectedness" of a variable in
a network, while density describes the networks' overall connectedness.
Specifically, it computes the in-strength, out-strength, contemporaneous
strength, temporal network density, and contemporaneous network density. The
result can then be visualized using plot_centrality
.
Usage
get_centrality(fitobj, burnin = 0, remove_ar = TRUE)
Arguments
fitobj |
Fitted model object for a Bayesian GVAR model. This can be
'tsnet_fit' object (obtained from |
burnin |
An integer specifying the number of initial samples to discard
as burn-in. Default is |
remove_ar |
A logical value specifying whether to remove the
autoregressive effects for centrality calculation. Default is |
Value
A list containing the following centrality measures:
-
instrength
: In-strength centrality. -
outstrength
: Out-strength centrality. -
strength
: Contemporaneous strength centrality. -
density_beta
: Temporal network density. -
density_pcor
: Contemporaneous network density.
Examples
# Use first individual from example fit data from tsnet
data(fit_data)
centrality_measures <- get_centrality(fit_data[[1]])