Extract Group Influence Trajectories — get_group_influence • dbn

Computes group influence trajectories with posterior quantiles

Usage

get_group_influence(
  fit,
  group,
  type = c("sender", "target"),
  measure = c("rowsum", "rowmean", "l2"),
  fun = c("mean", "sum"),
  probs = c(0.025, 0.5, 0.975)
)

Arguments

fit: A "dbn" object from dbn_dynamic()
group: Integer vector of actor indices
type: "sender" or "target"
measure: Per-actor metric: "rowsum", "rowmean", "l2"
fun: Aggregation across actors: "mean" or "sum"
probs: Quantile probabilities to compute

Value

Data frame with time, posterior quantiles, and mean

See also

plot_group_influence, compare_group_influence, dbn

Examples

# \donttest{
sim <- simulate_dynamic_dbn(n = 10, time = 10, seed = 6886)
fit <- dbn(sim$Z, model = "dynamic", family = "gaussian",
    nscan = 200, burn = 100, verbose = FALSE)
inf_data <- get_group_influence(fit, group = c(1, 3, 5), type = "sender")
# }