ryule: Generate a (non-random) network from a Yule Distribution
In degreenet: Models for Skewed Count Distributions Relevant to Networks

Description Usage Arguments Value Note References See Also Examples

Generate a network with a given number of actors having a degree distribution draw from a Yule distribution. The resultant network is not random - that is, is not a random draw from all such networks.

1	ryule(n=20,rho=2.5, maxdeg=n-1, maxit=10, verbose=FALSE)

`n`	Number of actors in the network.
`rho`	PDF exponent of the Yule distribution.
`maxdeg`	Maximum degree to sample (using truncation of the distribution). If this is greater then `n-1` then `n-1` is used.
`maxit`	integer; maximum number of resamplings of the degree sequence to find a valid network.
`verbose`	Print out details of the progress of the algorithm.

If the network package is available, the network is returned as a network object. If not a sociomatrix is returned.

See the working papers on http://www.csss.washington.edu/Papers for details

Jones, J. H. and Handcock, M. S. "An assessment of preferential attachment as a mechanism for human sexual network formation," Proceedings of the Royal Society, B, 2003, 270, 1123-1128.

ayulemle, dyule, reedmolloy

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# Now, simulate a Yule network of 30
# actors with rho=4.0
ryule(n=30, rho=4)

degreenet: Models for Skewed Count Distributions Relevant to Networks
Version 1.3-1 created on 2015-04-03.
copyright (c) 2013, Mark S. Handcock, University of California - Los Angeles
 Based on "statnet" project software (statnet.org).
 For license and citation information see statnet.org/attribution
 For citation information, type citation("degreenet").
 Type help("degreenet-package") to get started.

 Network attributes:
  vertices = 30 
  directed = FALSE 
  hyper = FALSE 
  loops = FALSE 
  multiple = FALSE 
  bipartite = FALSE 
  total edges= 24 
    missing edges= 0 
    non-missing edges= 24 

 Vertex attribute names: 
    vertex.names 

No edge attributes