Use this if you are using igraph from R
sample_last_cit
creates a graph, where vertices age, and
gain new connections based on how long ago their last citation
happened.
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(...)
n |
Number of vertices. |
edges |
Number of edges per step. |
agebins |
Number of aging bins. |
pref |
Vector ( |
directed |
Logical scalar, whether to generate directed networks. |
... |
Passed to the actual constructor. |
types |
Vector of length ‘ |
attr |
Logical scalar, whether to add the vertex types to the generated
graph as a vertex attribute called ‘ |
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 (potentially) cited
vertex only.
A new graph.
Gabor Csardi csardi.gabor@gmail.com