simpln: Simulate from a Poisson Lognormal Distribution

In degreenet: Models for Skewed Count Distributions Relevant to Networks

Description

Functions to generate random samples from a Poisson Lognormal Probability Distribution

Usage

simpln(n=100, v=c(0.6,1.2), maxdeg=10000, cutoff=1)

Arguments

n	number of samples to draw.
v	Poisson Lognormal parameters: lognormal mean and lognormal s.d.
maxdeg	Maximum degree to sample (using truncation of the distribution).
cutoff	Calculate estimates conditional on exceeding this value.

Value

vector of random draws or samples.

Note

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

aplnmle, dpln

Examples

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

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

Example output

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.

s4
 1  2  3  4  7 
59 28  9  3  1 

degreenet documentation built on May 1, 2019, 8:08 p.m.