igraph (version 1.1.1)

sample_last_cit: Random citation graphs

Description

sample_last_cit creates a graph, where vertices age, and gain new connections based on how long ago their last citation happened.

Usage

sample_last_cit(n, edges = 1, agebins = n/7100, pref = (1:(agebins +
  1))^-3, directed = TRUE)
last_cit(...)
sample_cit_types(n, edges = 1, types = rep(0, n), pref = rep(1,
  length(types)), directed = TRUE, attr = TRUE)
cit_types(...)
sample_cit_cit_types(n, edges = 1, types = rep(0, n), pref = matrix(1,
  nrow = length(types), ncol = length(types)), directed = TRUE, attr = TRUE)
cit_cit_types(...)

Arguments

n

Number of vertices.

edges

Number of edges per step.

agebins

Number of aging bins.

pref

Vector (sample_last_cit and sample_cit_types or matrix (sample_cit_cit_types) giving the (unnormalized) citation probabilities for the different vertex types.

directed

Logical scalar, whether to generate directed networks.

...

Passed to the actual constructor.

types

Vector of length ‘n’, the types of the vertices. Types are numbered from zero.

attr

Logical scalar, whether to add the vertex types to the generated graph as a vertex attribute called ‘type’.

Value

A new graph.

Details

sample_cit_cit_types is a stochastic block model where the graph is growing.

sample_cit_types is similarly a growing stochastic block model, but the probability of an edge depends on the (potentiall) cited vertex only.