Simulate a bipartite network

Usage

simulate_bipartite_network(
  actors,
  events,
  edges = NULL,
  probability = 0.1,
  weight = c("binary", "uniform", "normal", "poisson"),
  weight_mean = 1,
  weight_sd = 1,
  weight_range = c(0.1, 1),
  seed = NULL,
  batch = NULL
)

Arguments

actors: Number or labels of primary-mode nodes.
events: Number or labels of secondary-mode nodes.
edges: Optional exact number of cross-mode edges.
probability: Cross-mode edge probability when edges is NULL.
weight: Edge-weight distribution.
weight_mean, weight_sd, weight_range: Weight parameters.
seed: Optional seed.
batch: Optional single positive whole number. When given, the simulator runs batch times and returns a plain list of batch results, each exactly what the same call without batch returns. With a seed, every dataset gets its own seed drawn from seed, so the whole batch is reproducible; without one the datasets are consecutive draws from the session's random-number stream. The default NULL returns a single result.

Value

A tidy cross-mode edge-list simulab_sim base data.frame with one row per actor-event edge and columns from (always an actor), to (always an event), weight, from_mode, and to_mode. The two modes are disjoint, so no edge joins two actors or two events and self-loops cannot occur. as.data.frame(x, what = ) also returns nodes (node, mode), incidence (the wide actor-by-event incidence table: an actor column followed by one column per event), and a one-row settings table.

Examples

result <- simulate_bipartite_network(actors = 20, events = 6, probability = 0.3, seed = 1)
head(result)
#> <simulab_sim:bipartite_network> 6 rows x 5 columns
#>       from      to weight from_mode to_mode
#> 1  Actor 4 Event 1      1     actor   event
#> 2  Actor 6 Event 1      1     actor   event
#> 3  Actor 7 Event 1      1     actor   event
#> 4 Actor 15 Event 1      1     actor   event
#> 5 Actor 17 Event 1      1     actor   event
#> 6 Actor 18 Event 1      1     actor   event
#> 
#> Truth (settings):
#>   probability weight actors events
#> 1         0.3 binary     20      6
#> 
#> Other tables: nodes, incidence. Read one with as.data.frame(x, what = "nodes").
components(result)
#>       table rows columns
#> 1      data   37       5
#> 2     nodes   26       2
#> 3 incidence   20       7
#> 4  settings    1       4