Generate random graphs using preferential attachment

barabasi.game() was renamed to sample_pa() to create a more consistent API.

barabasi.game(
  n,
  power = 1,
  m = NULL,
  out.dist = NULL,
  out.seq = NULL,
  out.pref = FALSE,
  zero.appeal = 1,
  directed = TRUE,
  algorithm = c("psumtree", "psumtree-multiple", "bag"),
  start.graph = NULL
)

Arguments

n: Number of vertices.
power: The power of the preferential attachment, the default is one, i.e. linear preferential attachment.
m: Numeric constant, the number of edges to add in each time step This argument is only used if both out.dist and out.seq are omitted or NULL.
out.dist: Numeric vector, the distribution of the number of edges to add in each time step. This argument is only used if the out.seq argument is omitted or NULL.
out.seq: Numeric vector giving the number of edges to add in each time step. Its first element is ignored as no edges are added in the first time step.
out.pref: Logical, if true the total degree is used for calculating the citation probability, otherwise the in-degree is used.
zero.appeal: The ‘attractiveness’ of the vertices with no adjacent edges. See details below.
directed: Whether to create a directed graph.
algorithm: The algorithm to use for the graph generation. psumtree uses a partial prefix-sum tree to generate the graph, this algorithm can handle any power and zero.appeal values and never generates multiple edges. psumtree-multiple also uses a partial prefix-sum tree, but the generation of multiple edges is allowed. Before the 0.6 version igraph used this algorithm if power was not one, or zero.appeal was not one. bag is the algorithm that was previously (before version 0.6) used if power was one and zero.appeal was one as well. It works by putting the ids of the vertices into a bag (multiset, really), exactly as many times as their (in-)degree, plus once more. Then the required number of cited vertices are drawn from the bag, with replacement. This method might generate multiple edges. It only works if power and zero.appeal are equal one.
start.graph: NULL or an igraph graph. If a graph, then the supplied graph is used as a starting graph for the preferential attachment algorithm. The graph should have at least one vertex. If a graph is supplied here and the out.seq argument is not NULL, then it should contain the out degrees of the new vertices only, not the ones in the start.graph.