urhyper {Runuran}

UNU.RAN Hypergeometric random variate generator

Description

UNU.RAN random variate generator for the Hypergeometric distribution. It also allows sampling from the truncated distribution.

[Special Generator] – Sampling Function: Hypergeometric.

Usage

urhyper(nn, m, n, k, lb=max(0,k-n), ub=min(k,m))

Arguments

nn

number of observations.

m

the number of white balls in the urn.

n

the number of black balls in the urn.

k

the number of balls drawn from the urn.

lb

lower bound of (truncated) distribution.

ub

upper bound of (truncated) distribution.

Details

The Hypergeometric distribution is used for sampling without replacement. The density of this distribution with parameters m, n and k (named Np, N-Np, and n, respectively in the reference below) is given by

p(x) = \left. {m \choose x}{n \choose k-x} \right/ {m+n \choose k}

for x = 0, \ldots, k.

The generation algorithm uses guide table based inversion. The parameters lb and ub can be used to generate variates from the Hypergeometric distribution truncated to the interval (lb,ub).

Note

This function is a wrapper for the UNU.RAN class in R. Compared to rhyper, urhyper is faster, especially for larger sample sizes. However, in opposition to rhyper vector arguments are ignored, i.e. only the first entry is used.

Author(s)

Josef Leydold and Wolfgang H\"ormann [e-mail].

References

W. H\"ormann, J. Leydold, and G. Derflinger (2004): Automatic Nonuniform Random Variate Generation. Springer-Verlag, Berlin Heidelberg

See Also

runif and .Random.seed about random number generation, unuran for the UNU.RAN class, and rhyper for the R built-in generator.

Examples

## Create a sample of size 1000
x <- urhyper(nn=20,m=15,n=5,k=7)