simnb: Simulate from a Negative Binomial Distribution
In degreenet: Models for Skewed Count Distributions Relevant to Networks

Description Usage Arguments Value Note References See Also Examples

Functions to generate random samples from a Negative Binomial Probability Distribution

1	simnb(n=100, v=c(5,0.2), maxdeg=10000)

`n`	number of samples to draw.
`v`	Negative Binomial parameters: expected count and probability of another.
`maxdeg`	Maximum degree to sample (using truncation of the distribution).

vector of random draws or samples.

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.

anbmle, dnb

# Now, simulate a Negative Binomial distribution over 100
# observations with lognormal mean -1 and lognormal standard deviation 1.

set.seed(1)
s4 <- simnb(n=100, v=c(5,0.2))
table(s4)