| posterior_plot {tsnet} | R Documentation |
posterior_plot
Description
Plots posterior distributions of the parameters of the temporal or the contemporaneous networks of a GVAR model. The posterior distributions are visualized as densities in a matrix layout.
Usage
posterior_plot(fitobj, mat = "beta", cis = c(0.8, 0.9, 0.95))
Arguments
fitobj |
Fitted model object. This can be a tsnet_fit object (obtained from [stan_gvar()]) or a BGGM object (obtained from [BGGM::var_estimate()]). |
mat |
A matrix to use for plotting. Possibilities include "beta" (temporal network) and "pcor" (contemporaneous network). Default is "beta" (temporal network). |
cis |
A numeric vector of credible intervals to use for plotting. Default is c(0.8, 0.9, 0.95). |
Details
In the returned plot, posterior distributions for every parameter are shown. Lagged variables are displayed along the vertical line of the grid, and non-lagged variables along the horizontal line of the grids.
Value
A ggplot object representing the posterior distributions of the parameters of the temporal or the contemporaneous networks of a GVAR model.
Examples
# Load simulated time series data
data(ts_data)
example_data <- ts_data[1:100,1:4]
# Estimate a GVAR model
fit <- stan_gvar(example_data, n_chains = 2)
# Extract posterior samples
posterior_plot(fit)