simnb: Simulate from a Negative Binomial Distribution

In degreenet: Models for Skewed Count Distributions Relevant to Networks

Simulate from a Negative Binomial Distribution

Description

Functions to generate random samples from a Negative Binomial Probability Distribution

Usage

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

Arguments

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).

Value

vector of random draws or samples.

Note

See the papers on https://handcock.github.io/?q=Holland for details

References

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.

See Also

anbmle, dnb

Examples

# 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)

degreenet documentation built on Sept. 26, 2024, 1:08 a.m.