rpanet_general {wdnet} | R Documentation |
Internal functions for generating PA networks
Description
These functions generate a PA network with linear (rpanet_simple
) or
non-linear (rpanet_general
) preference functions
Usage
rpanet_general(
nstep,
initial.network,
control,
m,
sum_m,
w,
nnode,
nedge,
method,
sample.recip
)
rpanet_simple(
nstep,
initial.network,
control,
m,
sum_m,
w,
ex_node,
ex_edge,
method
)
Arguments
nstep |
Number of steps when generating a network. |
initial.network |
A |
control |
A list of parameters that controls the PA generation process.
The default value is |
m |
Integer vector, number of new edges in each step. |
sum_m |
Integer, summation of |
w |
Vector, weight of new edges. |
nnode |
Integer, number of nodes in |
nedge |
Integer, number of edges in |
method |
Which method to use when generating PA networks: "binary" or "linear". |
sample.recip |
Whether reciprocal edges will be added. |
Value
Returns a wdnet
object that includes the following components:
-
directed
: Logical, whether the network is directed. -
weighted
: Logical, whether the network is weighted. -
edgelist
: A two-column matrix representing the edges. -
edge.attr
: A data frame including edge weights and edge scenarios (0: from initial network; 1:alpha
; 2:beta
; 3:gamma
; 4:xi
; 5;rho
; 6: reciprocal edge). -
node.attr
: A data frame including node out- and in-strength, node source and target preference scores (for directed networks), node strength and preference scores (for undirected networks), and node group (if applicable). -
newedge
: The number of new edges at each step, including reciprocal edges. -
control
: Anrpacontrol
object that is used to generate the network.