The number of edges to add to the graph per time step.
type.dist
The distribution of the vertex types. This is assumed to be
stationary in time.
pref.matrix
A matrix giving the preferences of the given vertex
types. These should be probabilities, ie. numbers between zero and one.
directed
Logical constant, whether to generate directed graphs.
...
Passed to the constructor, sample_traits or
sample_traits_callaway.
k
The number of trials per time step, see details below.
Value
A new graph object.
Details
For sample_traits_callaway the simulation goes like this: in each
discrete time step a new vertex is added to the graph. The type of this
vertex is generated based on type.dist. Then two vertices are
selected uniformly randomly from the graph. The probability that they will
be connected depends on the types of these vertices and is taken from
pref.matrix. Then another two vertices are selected and this is
repeated edges.per.step times in each time step.
For sample_traits the simulation goes like this: a single vertex is
added at each time step. This new vertex tries to connect to k
vertices in the graph. The probability that such a connection is realized
depends on the types of the vertices involved and is taken from
pref.matrix.
# two types of vertices, they like only themselvesg1 <- sample_traits_callaway(1000, 2, pref.matrix=matrix( c(1,0,0,1), nc=2))
g2 <- sample_traits(1000, 2, k=2, pref.matrix=matrix( c(1,0,0,1), nc=2))