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Scale-free random graphs, from vertex fitness scores

Source: R/games.R
static.power.law.game.Rd

[Deprecated]

static.power.law.game() was renamed to sample_fitness_pl() to create a more consistent API.

Usage

static.power.law.game(
  no.of.nodes,
  no.of.edges,
  exponent.out,
  exponent.in = -1,
  loops = FALSE,
  multiple = FALSE,
  finite.size.correction = TRUE
)

Arguments

no.of.nodes

The number of vertices in the generated graph.

no.of.edges

The number of edges in the generated graph.

exponent.out

Numeric scalar, the power law exponent of the degree distribution. For directed graphs, this specifies the exponent of the out-degree distribution. It must be greater than or equal to 2. If you pass Inf here, you will get back an Erdős-Rényi random network.

exponent.in

Numeric scalar. If negative, the generated graph will be undirected. If greater than or equal to 2, this argument specifies the exponent of the in-degree distribution. If non-negative but less than 2, an error will be generated.

loops

Logical scalar, whether to allow loop edges in the graph.

multiple

Logical scalar, whether to allow multiple edges in the graph.

finite.size.correction

Logical scalar, whether to use the proposed finite size correction of Cho et al., see references below.

static_power_law_game()