aging.prefatt.game: Generate an evolving random graph with preferential attachment
and aging
Description
This function creates a random graph by simulation its
evolution. Each time a new vertex is added it creates a number of links
to old vertices and the probability that an old vertex is cited depends on
its in-degree (preferential attachment) and age.
The number of edges each new vertex creates (except the very
first vertex.
aging.type
Character string, the type of the function giving
probability that an old vertex is cited depending on its age. See
details below.
params
Named list, this gives the parameters of the
aging function selected by the aging.type
argument. See details below.
...
Additional arguments, these are passed to the graph
constructor.
Value
A new graph.
Details
This is discrete time step model, in each time step a new vertex is
added to the network. The new vertex cites a number (parameter
m) of other vertices. The probability that a vertex is cited is
proportional to the product of the in-degree of the node plus one and
the so-called aging function (aging.type arguments).
The exponential aging function decreases exponetially with age
with exponent aging.exp, its only parameter.
The powerlaw aging function decreases as a power law with age,
the exponent is given by the aging.exp parameter.