This set of games are build around different types of nodes and simulating their interaction. The nature of their algorithm is described in detail at the linked igraph documentation.

play_preference(
  n,
  n_types,
  p_type = rep(1, n_types),
  p_pref = matrix(1, n_types, n_types),
  fixed = FALSE,
  directed = TRUE,
  loops = FALSE
)

play_preference_asym(
  n,
  n_types,
  p_type = matrix(1, n_types, n_types),
  p_pref = matrix(1, n_types, n_types),
  loops = FALSE
)

play_bipartite(n1, n2, p, m, directed = TRUE, mode = "out")

play_traits(
  n,
  n_types,
  growth = 1,
  p_type = rep(1, n_types),
  p_pref = matrix(1, n_types, n_types),
  callaway = TRUE,
  directed = TRUE
)

play_citation_type(
  n,
  growth,
  types = rep(0, n),
  p_pref = rep(1, length(unique(types))),
  directed = TRUE
)

Arguments

n, n1, n2

The number of nodes in the graph. For bipartite graphs n1 and n2 specifies the number of nodes of each type.

n_types

The number of different node types in the graph

p_type

The probability that a node will be the given type. Either a vector or a matrix, depending on the game

p_pref

The probability that an edge will be made to a type. Either a vector or a matrix, depending on the game

fixed

Should n_types be understood as a fixed number of nodes for each type rather than as a probability

directed

Should the resulting graph be directed

loops

Are loop edges allowed

p

The probabilty of an edge occuring

m

The number of edges in the graph

mode

The flow direction of edges

growth

The number of edges added at each iteration

callaway

Use the callaway version of the trait based game

types

The type of each node in the graph, enumerated from 0

Value

A tbl_graph object

Functions

See also

Examples

plot(play_bipartite(20, 30, 0.4))