rpanet.internal: Internal functions for generating PA networks

In wdnet: Weighted and Directed Networks

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 wdnet object or a list that represents the initial network. By default, initial.network has one directed edge from node 1 to node 2 with weight 1. It may have the following components: a two-column matrix edgelist representing the edges; a vector edgeweight representing the weight of edges; a logical argument directed indicating whether the initial network is directed; an integer vector nodegroup representing the group of nodes. nodegroup is defined for directed networks, if NULL, all nodes from the seed network are considered from group 1.
control	A list of parameters that controls the PA generation process. The default value is wdnet:::rpa_control_default(). By default, in each step, a new edge of weight 1 is added from a new node A to an existing node B (alpha scenario), where $B is chosen with probability proportional to its in-strength + 1.
m	Integer vector, number of new edges in each step.
sum_m	Integer, summation of m.
w	Vector, weight of new edges.
nnode	Integer, number of nodes in initial.network.
nedge	Integer, number of edges in initial.network.
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: An rpacontrol object that is used to generate the network.

wdnet documentation built on May 29, 2024, 9:32 a.m.