# Multinomial: Multinomial distribution

## Description

Probability mass function and random generation for the multinomial distribution.

## Usage

dmnom(x, size, prob, log = FALSE)rmnom(n, size, prob)

## Arguments

x

$$k$$-column matrix of quantiles.

size

numeric vector; number of trials (zero or more).

prob

$$k$$-column numeric matrix; probability of success on each trial.

log

logical; if TRUE, probabilities p are given as log(p).

n

number of observations. If length(n) > 1, the length is taken to be the number required.

## Details

Probability mass function $$f(x) = \frac{n!}{\prod_{i=1}^k x_i} \prod_{i=1}^k p_i^{x_i}$$

## References

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

Binomial, Multinomial

## Examples

Run this code
# NOT RUN {
# Generating 10 random draws from multinomial distribution
# parametrized using a vector

(x <- rmnom(10, 3, c(1/3, 1/3, 1/3)))

# Results are consistent with dmultinom() from stats:

all.equal(dmultinom(x[1,], 3, c(1/3, 1/3, 1/3)),
dmnom(x[1, , drop = FALSE], 3, c(1/3, 1/3, 1/3)))

# }


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