MultiHypergeometric: Multivariate hypergeometric distribution

In extraDistr: Additional Univariate and Multivariate Distributions

Multivariate hypergeometric distribution

Description

Probability mass function and random generation for the multivariate hypergeometric distribution.

Usage

dmvhyper(x, n, k, log = FALSE)

rmvhyper(nn, n, k)

Arguments

x	m-column matrix of quantiles.
n	m-length vector or m-column matrix of numbers of balls in m colors.
k	the number of balls drawn from the urn.
log	logical; if TRUE, probabilities p are given as log(p).
nn	number of observations. If length(n) > 1, the length is taken to be the number required.

Details

Probability mass function

f(x) = \frac{\prod_{i=1}^m {n_i \choose x_i}}{{N \choose k}}

The multivariate hypergeometric distribution is generalization of hypergeometric distribution. It is used for sampling without replacement k out of N marbles in m colors, where each of the colors appears n_i times. Where k=\sum_{i=1}^m x_i, N=\sum_{i=1}^m n_i and k \le N.

References

Gentle, J.E. (2006). Random number generation and Monte Carlo methods. Springer.

See Also

Hypergeometric

Examples

# Generating 10 random draws from multivariate hypergeometric
# distribution parametrized using a vector

rmvhyper(10, c(10, 12, 5, 8, 11), 33)

extraDistr documentation built on May 29, 2024, 9:31 a.m.