nwring
Generate a ring-lattice network
Syntax
nwring
nodes
,
k(int)
[weights(p1, p2,...)
undirected
name(newnetname)
labs(lab1 lab2 ...)
xvars
ntimes(int)]
nodes |
number of nodes |
k(int) |
number of neighhbors on ring-lattice on each side |
weights(p1, p2,...) |
probabilities p_k for tie weights k |
undirected |
generate an undirected network; default = directed |
name(newnetname) |
name of the new network |
labs(lab1 lab2 …) |
overwrite node labels |
xvars |
generate Stata variables for the network |
ntimes(int) |
number of networks to be generated; default = 1 |
noreplace |
reserved; currently a no-op - the create/replace collision guard on name() already applies regardless |
Description
nwring generates a (un-)directed, (un-)weighted ring-lattice network. Each node is connected to k nodes on each side. Basically, each node has 2 * k neighbors in a ring structure.
With option weights(p1, p2,…) the command generates a weighted network. Here, p_k stands for the probability to sample tie weight k. The probabilities p1, p2…, pn do not necessarily have to sum up to one; they are standardized. For example, the following produces a ring-lattice network with 20 nodes, where each node is connected to two neighbors on each side. Furthermore, each one of these sampled ties gets assigned a tie weight because of option weights(). In this case, weights(0.0, 0.3,0.7) indicates that tie weight 1 should be sampled with probability 0.0, tie weight 2 with probability 0.3 and tie weight 3 with probability 0.7.
. nwring 20, k(2) weights(0.0,0.3,0.7)
Examples
. nwclear
. nwring 20, k(2) undirected
Supported network types
Binary: yes (only structural tie placement - see Weighted). Directed: yes, via undirected (default is directed). Weighted: yes, via weights(), independent of the ring/shortcut placement mechanism itself. Signed: not checked. Two-mode: not applicable - this generator always produces a one-mode network.
Stored results
- nwring stores the following in r():
Macros
- r(netlist) list of new networks