Skip to contents

Network Snapshot

Source: R/post_methods.R
net_snapshot.Rd

Heat map of Theta at given time (posterior mean)

Usage

net_snapshot(
  fit,
  t,
  rel = 1,
  sparse = NULL,
  eps = 1e-04,
  show_significant = FALSE,
  cred_level = 0.025
)

Arguments

fit

Dynamic dbn object

t

Time point

rel

Relation index (default: 1)

sparse

Auto-switch to sparse visualization for large networks

eps

Threshold for sparse plotting

show_significant

Logical, whether to show only significant effects (default: FALSE)

cred_level

Credible level for significance (default corresponds to 95% CI)

Value

ggplot2 object or base R plot

See also

dbn, dyad_path, theta_summary, role_trajectory

Examples

# \donttest{
sim <- simulate_dynamic_dbn(n = 6, time = 10, seed = 1)
fit <- dbn(sim$Y, model = "dynamic", nscan = 200, burn = 100, verbose = FALSE)
net_snapshot(fit, t = 5)

# }