# Multinomial: Multinomial distribution In extraDistr: Additional Univariate and Multivariate Distributions

## Description

Probability mass function and random generation for the multinomial distribution.

## Usage

 ```1 2 3``` ```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) = n!/prod(x[i]!) * prod(p[i]^x[i])

## References

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

`Binomial`, `Multinomial`
 ```1 2 3 4 5 6 7 8 9``` ```# 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))) ```